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would you mind picking up the pizza that's on the chair, please?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance would you mind picking up the pizza that's on the chair, please? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
would you mind picking up the pizza that's on the chair, please? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
if you have a moment, could you please pick up the pizza on the chair?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance if you have a moment, could you please pick up the pizza on the chair? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
if you have a moment, could you please pick up the pizza on the chair? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you do me a favor and pick up the pizza from the chair?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you do me a favor and pick up the pizza from the chair? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
could you do me a favor and pick up the pizza from the chair? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
would it be possible for you to pick up the pizza that is on the chair?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance would it be possible for you to pick up the pizza that is on the chair? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
would it be possible for you to pick up the pizza that is on the chair? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
it would be really helpful if you could pick up the pizza from the chair.
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance it would be really helpful if you could pick up the pizza from the chair. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
it would be really helpful if you could pick up the pizza from the chair. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
please to take pizza from chair.
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance please to take pizza from chair. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
please to take pizza from chair. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
on chair, pizza you get.
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance on chair, pizza you get. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
on chair, pizza you get. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you, pizza on chair, pick up?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you, pizza on chair, pick up? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
could you, pizza on chair, pick up? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
chair, on it, pizza. please to collect.
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance chair, on it, pizza. please to collect. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
chair, on it, pizza. please to collect. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
one favor, pizza on chair, can you lift?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance one favor, pizza on chair, can you lift? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
one favor, pizza on chair, can you lift? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
grab the pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance grab the pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
grab the pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
fetch the pizza from the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance fetch the pizza from the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
fetch the pizza from the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
can you get the pizza off the chair?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance can you get the pizza off the chair? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
can you get the pizza off the chair? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
snag the pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance snag the pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
snag the pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
yo, get the chair pizza
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance yo, get the chair pizza ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
yo, get the chair pizza Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
um, pick up the, uh, pizza on the, um, chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance um, pick up the, uh, pizza on the, um, chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
um, pick up the, uh, pizza on the, um, chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
pick up the, um, pick up the pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance pick up the, um, pick up the pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
pick up the, um, pick up the pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
pick up the pizza on the, uh, chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance pick up the pizza on the, uh, chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
pick up the pizza on the, uh, chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
uh, pick up the, uh, pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance uh, pick up the, uh, pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
uh, pick up the, uh, pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
pick up the, um, uh, pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance pick up the, um, uh, pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
pick up the, um, uh, pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
take the pizza from the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance take the pizza from the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
take the pizza from the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
retrieve the pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance retrieve the pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
retrieve the pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
collect the pizza from the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance collect the pizza from the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
collect the pizza from the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
get the pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance get the pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
get the pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
pick up the pizza on the chair
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{pizza(VAR0),chair(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']
style:NoStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance pick up the pizza on the chair ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
pick up the pizza on the chair Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['pizza(VAR0)', 'chair(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you please pick up the chair that's to the right of the banana?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you please pick up the chair that's to the right of the banana? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
could you please pick up the chair that's to the right of the banana? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
would you mind grabbing the chair located to the right of the banana?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance would you mind grabbing the chair located to the right of the banana? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
would you mind grabbing the chair located to the right of the banana? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
if possible, could you take hold of the chair that is situated to the right of the banana?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance if possible, could you take hold of the chair that is situated to the right of the banana? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
if possible, could you take hold of the chair that is situated to the right of the banana? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
would it be too much trouble for you to collect the chair that's positioned to the right of the banana?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance would it be too much trouble for you to collect the chair that's positioned to the right of the banana? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
would it be too much trouble for you to collect the chair that's positioned to the right of the banana? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
if it's not too inconvenient, could you retrieve the chair that's to the right of the banana?
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance if it's not too inconvenient, could you retrieve the chair that's to the right of the banana? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
if it's not too inconvenient, could you retrieve the chair that's to the right of the banana? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
take chair to right side of banana please
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance take chair to right side of banana please ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
take chair to right side of banana please Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
grabbing chair, it is right of banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance grabbing chair, it is right of banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
grabbing chair, it is right of banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
please, chair is right side of banana, take it
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance please, chair is right side of banana, take it ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
please, chair is right side of banana, take it Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
banana to the left, chair to the right, please take
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance banana to the left, chair to the right, please take ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
banana to the left, chair to the right, please take Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
chair to right of banana, kindly grab
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance chair to right of banana, kindly grab ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
chair to right of banana, kindly grab Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
grab the chair next to the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance grab the chair next to the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
grab the chair next to the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
get the chair on the right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance get the chair on the right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
get the chair on the right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
yo, get the chair by the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance yo, get the chair by the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
yo, get the chair by the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
pick up the chair beside the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance pick up the chair beside the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
pick up the chair beside the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
hey, snatch the chair next to that banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance hey, snatch the chair next to that banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
hey, snatch the chair next to that banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
um, grab the chair, you know, right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance um, grab the chair, you know, right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
um, grab the chair, you know, right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
grab, uh, the chair right of the, uh, banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance grab, uh, the chair right of the, uh, banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
grab, uh, the chair right of the, uh, banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
grab the chair... well, right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance grab the chair... well, right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
grab the chair... well, right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
so, grab the, um, chair, right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance so, grab the, um, chair, right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
so, grab the, um, chair, right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
i mean, grab the chair, right of the, uh, banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance i mean, grab the chair, right of the, uh, banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
i mean, grab the chair, right of the, uh, banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
seize the seat to the right of the fruit
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance seize the seat to the right of the fruit ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
seize the seat to the right of the fruit Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
take hold of the chair on the right side of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance take hold of the chair on the right side of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
take hold of the chair on the right side of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
snatch the furniture piece next to the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance snatch the furniture piece next to the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
snatch the furniture piece next to the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
get the chair that's to the right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance get the chair that's to the right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
get the chair that's to the right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
pick up the chair located on the right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance pick up the chair located on the right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
pick up the chair located on the right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
grab the chair right of the banana
INSTRUCT(tyler,self:agent,take(self:agent,VAR0),{chair(VAR0),banana(VAR1),DEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
INSTRUCT
take(self:agent,VAR0)
['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']
style:NoStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance grab the chair right of the banana ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
grab the chair right of the banana Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'take(self:agent,VAR0)', 'supplemental_semantics': ['chair(VAR0)', 'banana(VAR1)', 'DEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you possibly place a tennis racket in front of the mouse?
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you possibly place a tennis racket in front of the mouse? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
could you possibly place a tennis racket in front of the mouse? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
would you mind setting a tennis racket in front of the mouse?
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance would you mind setting a tennis racket in front of the mouse? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
would you mind setting a tennis racket in front of the mouse? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
it would be great if you could put a tennis racket in front of the mouse.
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance it would be great if you could put a tennis racket in front of the mouse. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
it would be great if you could put a tennis racket in front of the mouse. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
i would appreciate it if you could set a tennis racket in front of the mouse.
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance i would appreciate it if you could set a tennis racket in front of the mouse. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
i would appreciate it if you could set a tennis racket in front of the mouse. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
if it's not too much trouble, could you set a tennis racket in front of the mouse?
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance if it's not too much trouble, could you set a tennis racket in front of the mouse? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
if it's not too much trouble, could you set a tennis racket in front of the mouse? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
put tennis racket in front mouse, please
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance put tennis racket in front mouse, please ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
put tennis racket in front mouse, please Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
mouse, in its front, you put tennis racket?
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance mouse, in its front, you put tennis racket? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
mouse, in its front, you put tennis racket? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you arranging tennis racket in mouse front?
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you arranging tennis racket in mouse front? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
could you arranging tennis racket in mouse front? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
in front of mouse, tennis racket is to be placed, yes?
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance in front of mouse, tennis racket is to be placed, yes? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
in front of mouse, tennis racket is to be placed, yes? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
do the setting of tennis racket, in front of this mouse please.
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance do the setting of tennis racket, in front of this mouse please. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
do the setting of tennis racket, in front of this mouse please. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
put a tennis racket near the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance put a tennis racket near the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
put a tennis racket near the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
get a tennis racket up close to the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance get a tennis racket up close to the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
get a tennis racket up close to the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
just place a tennis racket right by the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance just place a tennis racket right by the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
just place a tennis racket right by the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
throw a tennis racket in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance throw a tennis racket in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
throw a tennis racket in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
stick a tennis racket in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance stick a tennis racket in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
stick a tennis racket in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
uh, set a, um, tennis racket in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance uh, set a, um, tennis racket in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
uh, set a, um, tennis racket in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
set a tennis, um, racket in front... of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance set a tennis, um, racket in front... of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
set a tennis, um, racket in front... of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
so, set a tennis racket in, um, front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance so, set a tennis racket in, um, front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
so, set a tennis racket in, um, front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
set a tennis, uh, i mean racket, in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance set a tennis, uh, i mean racket, in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
set a tennis, uh, i mean racket, in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
hmm, set a tennis racket, uh, in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance hmm, set a tennis racket, uh, in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
hmm, set a tennis racket, uh, in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
place a tennis paddle before the rodent
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance place a tennis paddle before the rodent ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
place a tennis paddle before the rodent Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
put a tennis bat in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance put a tennis bat in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
put a tennis bat in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
position a tennis racquet in front of the small creature
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance position a tennis racquet in front of the small creature ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
position a tennis racquet in front of the small creature Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
situate a tennis bat before the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance situate a tennis bat before the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
situate a tennis bat before the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
arrange a racquet for tennis ahead of the rodent
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance arrange a racquet for tennis ahead of the rodent ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
arrange a racquet for tennis ahead of the rodent Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
set a tennis racket in front of the mouse
INSTRUCT(tyler,self:agent,putinfrontof(self:agent,VAR0,VAR1),{tennisracket(VAR0),mouse(VAR1),INDEFINITE(VAR0),DEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
putinfrontof(self:agent,VAR0,VAR1)
['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']
style:NoStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance set a tennis racket in front of the mouse ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
set a tennis racket in front of the mouse Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'putinfrontof(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['tennisracket(VAR0)', 'mouse(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you please place a broccoli on the traffic light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you please place a broccoli on the traffic light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
could you please place a broccoli on the traffic light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
would it be possible for you to set a broccoli on the traffic light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance would it be possible for you to set a broccoli on the traffic light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
would it be possible for you to set a broccoli on the traffic light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
i was wondering if you could put a broccoli on the traffic light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance i was wondering if you could put a broccoli on the traffic light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
i was wondering if you could put a broccoli on the traffic light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
do you think you could arrange a broccoli on the traffic light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance do you think you could arrange a broccoli on the traffic light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
do you think you could arrange a broccoli on the traffic light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
may i ask you to position a broccoli on the traffic light please?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DirectnessStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance may i ask you to position a broccoli on the traffic light please? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
may i ask you to position a broccoli on the traffic light please? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
please, to put a broccoli on traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance please, to put a broccoli on traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
please, to put a broccoli on traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
kindly set one broccoli to the traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance kindly set one broccoli to the traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
kindly set one broccoli to the traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
could you place single broccoli on top traffic light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance could you place single broccoli on top traffic light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
could you place single broccoli on top traffic light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
one broccoli, can put on traffic light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance one broccoli, can put on traffic light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
one broccoli, can put on traffic light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
you can set a broccoli on the signal light?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FamiliarityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance you can set a broccoli on the signal light? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
you can set a broccoli on the signal light? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
put a broccoli on the traffic light lol
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance put a broccoli on the traffic light lol ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
put a broccoli on the traffic light lol Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
someone drop a broccoli on that traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance someone drop a broccoli on that traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
someone drop a broccoli on that traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
broccoli on a traffic light? why not!
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance broccoli on a traffic light? why not! ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
broccoli on a traffic light? why not! Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
traffic light needs a broccoli, you feel?
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance traffic light needs a broccoli, you feel? ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
traffic light needs a broccoli, you feel? Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
let's slap a broccoli on that traffic light.
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:FormalityStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance let's slap a broccoli on that traffic light. ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
let's slap a broccoli on that traffic light. Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
uh, set a, um, broccoli on a, um, traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance uh, set a, um, broccoli on a, um, traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
uh, set a, um, broccoli on a, um, traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
so, set a broccoli, um, on a traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance so, set a broccoli, um, on a traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
so, set a broccoli, um, on a traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
i mean, set a broccoli on a...uh...traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance i mean, set a broccoli on a...uh...traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
i mean, set a broccoli on a...uh...traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
set a, uh, broccoli on a, like, traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance set a, uh, broccoli on a, like, traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
set a, uh, broccoli on a, like, traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
set a...hmm...broccoli on a traffic light
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:DisfluencyStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance set a...hmm...broccoli on a traffic light ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
set a...hmm...broccoli on a traffic light Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
place a broccoli on a stoplight
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance place a broccoli on a stoplight ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
place a broccoli on a stoplight Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
put a broccoli on a traffic signal
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance put a broccoli on a traffic signal ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
put a broccoli on a traffic signal Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }
position a broccoli on a traffic lamp
INSTRUCT(tyler,self:agent,puton(self:agent,VAR0,VAR1),{broccoli(VAR0),trafficlight(VAR1),INDEFINITE(VAR0),INDEFINITE(VAR1)})
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
INSTRUCT
puton(self:agent,VAR0,VAR1)
['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']
style:WordChoiceStyleAugmenter
null
['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong']
['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
### instruction {instruction_with_context} ### example {example_with_context} ### utterance {utterance} ### actions {actions} ### properties {properties} ### JSON: {output}
### instruction Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. ### example Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: {actions} detection capabilities: {properties} JSON: {{ "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }} ### utterance position a broccoli on a traffic lamp ### actions ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] ### properties ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] ### JSON: {'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
position a broccoli on a traffic lamp Available actions: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] Available detectors: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these']
{'intent': 'INSTRUCT', 'central_proposition': 'puton(self:agent,VAR0,VAR1)', 'supplemental_semantics': ['broccoli(VAR0)', 'trafficlight(VAR1)', 'INDEFINITE(VAR0)']}
Given an utterance and a context comprising a set of action and detection capabilities, extract a semantic parse of the utterance commensurate with the actions and detection abilities, and respond with the parse in a perfect JSON format. Here is an example of a parse for an utterance. utterance: put the potted plant outside of the skis action capabilities: ['startVisualSearch', 'handleGreeting', 'getTime', 'initSearchesDemo', 'putinside', 'puton', 'putleftof', 'putbehind', 'stopVisualSearch', 'clearrelations', 'translateLastGoal', 'putagainst', 'putoutside', 'putalong', 'take', 'lookForObject', 'putbeside', 'initSearches', 'putrightof', 'getCurrGoals', 'putallover', 'handleAck', 'putbelow', 'putbetween', 'putinfrontof', 'findGraspableObject', 'putabove', 'findObject', 'putamong'] detection capabilities: ['doit', 'dothis', 'dothat', 'that', 'this', 'physobj', 'at', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush', 'blue', 'red', 'yellow', 'heavy', "evan's", "vasanth's", 'it', 'this', 'that', 'thing', 'those', 'they', 'these', 'this', 'it', 'that', 'thing', 'those', 'they', 'these'] JSON: { "intent": "INSTRUCT", "central_proposition": "putoutside(self:agent,VAR0,VAR1)", "supplemental_semantics": [[ "pottedplant(VAR0)", "skis(VAR1)", "DEFINITE(VAR0)", "DEFINITE(VAR1)" ]] }