Question Answering
English
JamshidJDMY commited on
Commit
0e4d760
verified
1 Parent(s): f4af940

Upload 5 files

Browse files
datasets/hintqa.pickle CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:c56b23d510456dca12e37b47e5b4337b9759c66e34214ba6bdc4745f5b3e8ce1
3
- size 55383770
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f8e58f86e93367caaf2508047fa2e5859a60754ad4811c30247e53d61746eeb3
3
+ size 55383750
datasets/kg-hint.pickle CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d40ba25c2ed48661d708f440423d0cb84224266128fc52aa705970871650bcec
3
  size 66070
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ed988defd1f612016e485853206ead60c33d38dddb319aaf1ed335141335e67b
3
  size 66070
datasets/metadata.json CHANGED
@@ -1 +1 @@
1
- {"hintqa": {"name": "HintQA", "version": "1.0", "description": "This dataset is generated using the method proposed in the TriviaHG paper for the test set questions of TriviaQA, NQ, and WebQ datasets. For each question, up to seven hints are generated and evaluated using various metrics.", "url": "https://github.com/DataScienceUIBK/HintQA", "subsets": {"WebQ-Vanilla": {"questions": 2032, "hints": 15812}, "WebQ-Finetuned": {"questions": 2032, "hints": 16978}, "NQ-Vanilla": {"questions": 3610, "hints": 30976}, "NQ-Finetuned": {"questions": 3610, "hints": 33131}, "TriviaQA-Vanilla": {"questions": 11313, "hints": 103018}, "TriviaQA-Finetuned": {"questions": 11313, "hints": 105709}}}, "kg-hint": {"name": "KG-Hint", "version": "1.0", "description": "This dataset is generated using the AutomaticHintGeneration system. The system processes an .xlsx file containing the question, answer, and category. It retrieves information related to the answer from Wikidata and Wikipedia to generate hints. The answer must be a Wikipedia entity and can be a person, year, or location.", "url": "https://dl.acm.org/doi/10.1145/3578337.3605119", "subsets": {"entire": {"questions": 30, "hints": 307}}}, "triviahg": {"name": "TriviaHG", "version": "1.0", "description": "TriviaHG is an extensive dataset crafted specifically for hint generation in question answering.", "url": "https://github.com/DataScienceUIBK/TriviaHG", "subsets": {"LLaMA_13b_Vanilla": {"questions": 100, "hints": 896}, "WizardLM_70b": {"questions": 100, "hints": 941}, "GPT_4": {"questions": 100, "hints": 949}, "Copilot": {"questions": 100, "hints": 970}, "LLaMA_70b_Finetuned": {"questions": 100, "hints": 924}, "LLaMA_70b_Vanilla": {"questions": 100, "hints": 683}, "Gemini": {"questions": 100, "hints": 942}, "LLaMA_7b_Finetuned": {"questions": 100, "hints": 923}, "LLaMA_7b_Vanilla": {"questions": 100, "hints": 840}, "LLaMA_13b_Finetuned": {"questions": 100, "hints": 921}, "GPT_3.5": {"questions": 100, "hints": 898}, "test": {"questions": 1000, "hints": 9617}, "validation": {"questions": 1000, "hints": 9638}, "training": {"questions": 14645, "hints": 140973}}}, "wikihint": {"name": "WikiHint", "version": "1.0", "description": "The dataset was created using Amazon Mechanical Turk (MTurk). Workers were instructed to write five hints based on a Wikipedia article as their knowledge base. After writing all five hints, they ranked their hints by usefulness. A hint is ranked higher if it is more likely to lead the user to the correct answer. The best hint is assigned a rank of 1, and the worst hint is assigned a rank of 5.", "url": "https://github.com/FloGerhold/Hint_Dataset", "subsets": {"train": {"questions": 900, "hints": 4500}, "test": {"questions": 100, "hints": 500}, "LLaMA-3.1-8b-FTwA-answer-aware": {"questions": 100, "hints": 100}, "GPT-4-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "GPT-4-Vanilla-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-8b-Vanilla-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-405b-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-8b-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-FTwA-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-FTwoA-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-405b-Vanilla-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-8b-FTwoA-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-Vanilla-answer-aware": {"questions": 100, "hints": 100}}}}
 
1
+ {"hintqa": {"name": "HintQA", "version": "1.0", "description": "This dataset is generated using the method proposed in the TriviaHG paper for the test set questions of TriviaQA, NQ, and WebQ datasets. For each question, up to seven hints are generated and evaluated using various metrics.", "url": "https://aclanthology.org/2024.findings-emnlp.546/", "subsets": {"WebQ-Vanilla": {"questions": 2032, "hints": 15812}, "WebQ-Finetuned": {"questions": 2032, "hints": 16978}, "NQ-Vanilla": {"questions": 3610, "hints": 30976}, "NQ-Finetuned": {"questions": 3610, "hints": 33131}, "TriviaQA-Vanilla": {"questions": 11313, "hints": 103018}, "TriviaQA-Finetuned": {"questions": 11313, "hints": 105709}}}, "kg-hint": {"name": "KG-Hint", "version": "1.0", "description": "This dataset is generated using the AutomaticHintGeneration system. The system processes an .xlsx file containing the question, answer, and category. It retrieves information related to the answer from Wikidata and Wikipedia to generate hints. The answer must be a Wikipedia entity and can be a person, year, or location.", "url": "https://dl.acm.org/doi/10.1145/3578337.3605119", "subsets": {"entire": {"questions": 30, "hints": 307}}}, "triviahg": {"name": "TriviaHG", "version": "1.0", "description": "TriviaHG is an extensive dataset crafted specifically for hint generation in question answering.", "url": "https://dl.acm.org/doi/abs/10.1145/3626772.3657855", "subsets": {"LLaMA_13b_Vanilla": {"questions": 100, "hints": 896}, "WizardLM_70b": {"questions": 100, "hints": 941}, "GPT_4": {"questions": 100, "hints": 949}, "Copilot": {"questions": 100, "hints": 970}, "LLaMA_70b_Finetuned": {"questions": 100, "hints": 924}, "LLaMA_70b_Vanilla": {"questions": 100, "hints": 683}, "Gemini": {"questions": 100, "hints": 942}, "LLaMA_7b_Finetuned": {"questions": 100, "hints": 923}, "LLaMA_7b_Vanilla": {"questions": 100, "hints": 840}, "LLaMA_13b_Finetuned": {"questions": 100, "hints": 921}, "GPT_3.5": {"questions": 100, "hints": 898}, "test": {"questions": 1000, "hints": 9617}, "validation": {"questions": 1000, "hints": 9638}, "training": {"questions": 14645, "hints": 140973}}}, "wikihint": {"name": "WikiHint", "version": "1.0", "description": "The dataset was created using Amazon Mechanical Turk (MTurk). Workers were instructed to write five hints based on a Wikipedia article as their knowledge base. After writing all five hints, they ranked their hints by usefulness. A hint is ranked higher if it is more likely to lead the user to the correct answer. The best hint is assigned a rank of 1, and the worst hint is assigned a rank of 5.", "url": "https://github.com/FloGerhold/Hint_Dataset", "subsets": {"train": {"questions": 900, "hints": 4500}, "test": {"questions": 100, "hints": 500}, "LLaMA-3.1-8b-FTwA-answer-aware": {"questions": 100, "hints": 100}, "GPT-4-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "GPT-4-Vanilla-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-8b-Vanilla-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-405b-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-8b-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-FTwA-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-FTwoA-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-405b-Vanilla-answer-aware": {"questions": 100, "hints": 100}, "LLaMA-3.1-8b-FTwoA-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-Vanilla-answer-agnostic": {"questions": 100, "hints": 100}, "LLaMA-3.1-70b-Vanilla-answer-aware": {"questions": 100, "hints": 100}}}}
datasets/triviahg.pickle CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:077ad5ac5a7e918184c7f48a917ecbbb71f41442976e15e877b683e6671d7652
3
- size 40273077
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:25e3a330d9f38f9c52e102d3a4cb633905d4300492484c4892e490fc7958f702
3
+ size 40273088
datasets/wikihint.pickle CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a2fe7e79ed85206409ae11b9d95c32934af2d2a6d20752f8cb9cb6346860d9cd
3
  size 1931395
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a67e0c1c52b4a6030ff3692dff8c6cb021fc74d0610395f419aa300338c341ba
3
  size 1931395