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stringlengths 7
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stringlengths 7
978
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stringclasses 79
values | negative_labels
stringclasses 55
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stringlengths 14
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RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Eruptive epidermoid cysts resulting from treatment with imiquimod .
|
adverse effect: Eruptive epidermoid cysts -> imiquimod
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Eruptive epidermoid cysts", "relation": "adverse effect", "tail": "imiquimod"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Bronchiolitis obliterans organising pneumonia associated with the use of nitrofurantoin .
|
adverse effect: Bronchiolitis obliterans organising pneumonia -> nitrofurantoin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Bronchiolitis obliterans organising pneumonia", "relation": "adverse effect", "tail": "nitrofurantoin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
We report the case of a young healthy woman who presented an early overanticoagulation when receiving acenocoumarol for a first thromboembolic episode .
|
adverse effect: overanticoagulation -> acenocoumarol
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "overanticoagulation", "relation": "adverse effect", "tail": "acenocoumarol"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Hypersensitivity to aspirin can be manifested as acute asthma , urticaria and/or angioedema , or a systemic anaphylactoid reaction .
|
adverse effect: systemic anaphylactoid reaction -> aspirin | adverse effect: angioedema -> aspirin | adverse effect: urticaria -> aspirin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "angioedema", "relation": "adverse effect", "tail": "aspirin"}, {"head": "systemic anaphylactoid reaction", "relation": "adverse effect", "tail": "aspirin"}, {"head": "urticaria", "relation": "adverse effect", "tail": "aspirin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Prick tests and intradermal tests with a series of dilutions of carboplatin and cisplatin were performed on three patients who had exhibited medium and severe hypersensitivity reactions to carboplatin .
|
adverse effect: severe hypersensitivity -> carboplatin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "severe hypersensitivity", "relation": "adverse effect", "tail": "carboplatin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Although the data indicate an immune - complex cause for gold - salt nephropathy , the incident antigen ( or antigens ) and mechanism of action remain unidentified .
|
adverse effect: nephropathy -> gold - salt
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "nephropathy", "relation": "adverse effect", "tail": "gold - salt"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Phenylpropanolamine ( PPA ) recently has been publicly implicated as a cause of stroke and other neurologic events .
|
adverse effect: stroke -> Phenylpropanolamine | adverse effect: stroke -> PPA | adverse effect: neurologic events -> PPA | adverse effect: neurologic events -> Phenylpropanolamine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "neurologic events", "relation": "adverse effect", "tail": "Phenylpropanolamine"}, {"head": "neurologic events", "relation": "adverse effect", "tail": "PPA"}, {"head": "stroke", "relation": "adverse effect", "tail": "Phenylpropanolamine"}, {"head": "stroke", "relation": "adverse effect", "tail": "PPA"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Multiple complications of propylthiouracil treatment : granulocytopenia , eosinophilia , skin reaction and hepatitis with lymphocyte sensitization .
|
adverse effect: lymphocyte sensitization -> propylthiouracil | adverse effect: eosinophilia -> propylthiouracil | adverse effect: hepatitis -> propylthiouracil | adverse effect: skin reaction -> propylthiouracil | adverse effect: granulocytopenia -> propylthiouracil
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "eosinophilia", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "granulocytopenia", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "hepatitis", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "lymphocyte sensitization", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "skin reaction", "relation": "adverse effect", "tail": "propylthiouracil"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Hence , hyperthyroidism induced by IFN - alpha could correspond to the first phase of silent thyroiditis , to Graves ' disease or to the succession of both .
|
adverse effect: hyperthyroidism -> IFN - alpha
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "hyperthyroidism", "relation": "adverse effect", "tail": "IFN - alpha"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
This regimen could prove useful for other patients who develop hypersensitivity reactions to carboplatin and allow therapy to continue .
|
adverse effect: hypersensitivity -> carboplatin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "hypersensitivity", "relation": "adverse effect", "tail": "carboplatin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Thus , an immunological mechanism might be involved in the mechanism of pirmenol - induced QT prolongation and T wave inversion on the electrocardiogram .
|
adverse effect: QT prolongation -> pirmenol | adverse effect: T wave inversion -> pirmenol
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "QT prolongation", "relation": "adverse effect", "tail": "pirmenol"}, {"head": "T wave inversion", "relation": "adverse effect", "tail": "pirmenol"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Magnesium tocolysis as the cause of urinary calculus during pregnancy .
|
adverse effect: urinary calculus -> Magnesium
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "urinary calculus", "relation": "adverse effect", "tail": "Magnesium"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
A case of tuberculosis in a patient on Efalizumab and Etanercept for treatment of refractory palmopustular psoriasis and psoriatic arthritis .
|
adverse effect: tuberculosis -> Efalizumab | adverse effect: tuberculosis -> Etanercept
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "tuberculosis", "relation": "adverse effect", "tail": "Efalizumab"}, {"head": "tuberculosis", "relation": "adverse effect", "tail": "Etanercept"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
OBJECTIVES : The authors described a case of Hashimoto 's disease during interferon - alpha ( IFN - alpha ) treatment for chronic viral C hepatitis in a patient with the specific genetic susceptibility associated with the thyroid disease .
|
adverse effect: Hashimoto 's disease -> IFN - alpha | adverse effect: Hashimoto 's disease -> interferon - alpha
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Hashimoto 's disease", "relation": "adverse effect", "tail": "IFN - alpha"}, {"head": "Hashimoto 's disease", "relation": "adverse effect", "tail": "interferon - alpha"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Hepatic damage after danazol treatment .
|
adverse effect: Hepatic damage -> danazol
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Hepatic damage", "relation": "adverse effect", "tail": "danazol"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Niacin maculopathy .
|
adverse effect: maculopathy -> Niacin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "maculopathy", "relation": "adverse effect", "tail": "Niacin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Angioedema and dysphagia caused by contact allergy to inhaled budesonide .
|
adverse effect: Angioedema -> budesonide | adverse effect: dysphagia -> budesonide
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Angioedema", "relation": "adverse effect", "tail": "budesonide"}, {"head": "dysphagia", "relation": "adverse effect", "tail": "budesonide"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
OBSERVATIONS : A 48-year - old woman presented with disfiguring facial edema 10 weeks after she began antiviral therapy with peginterferon alfa-2a and ribavirin for chronic hepatitis C infection .
|
adverse effect: disfiguring facial edema -> ribavirin | adverse effect: disfiguring facial edema -> peginterferon alfa-2a
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "disfiguring facial edema", "relation": "adverse effect", "tail": "peginterferon alfa-2a"}, {"head": "disfiguring facial edema", "relation": "adverse effect", "tail": "ribavirin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
A case report is presented concerning the administration of ketanserin in the treatment of pulmonary vasoconstriction and right ventricular failure following the infusion of protamine in a patient undergoing coronary artery bypass surgery and mitral valve replacement .
|
adverse effect: right ventricular failure -> protamine | adverse effect: pulmonary vasoconstriction -> protamine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "pulmonary vasoconstriction", "relation": "adverse effect", "tail": "protamine"}, {"head": "right ventricular failure", "relation": "adverse effect", "tail": "protamine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Fatal pulmonary fibrosis associated with BCNU : the relative role of platelet - derived growth factor - B , insulin - like growth factor I , transforming growth factor - beta1 and cyclooxygenase-2 .
|
adverse effect: Fatal pulmonary fibrosis -> BCNU
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Fatal pulmonary fibrosis", "relation": "adverse effect", "tail": "BCNU"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Syncope in a 65-year - old woman after nitrate ingestion .
|
adverse effect: Syncope -> nitrate
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Syncope", "relation": "adverse effect", "tail": "nitrate"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
A 57-year - old man developed morphea while taking bromocriptine .
|
adverse effect: morphea -> bromocriptine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "morphea", "relation": "adverse effect", "tail": "bromocriptine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Hydrocortisone may decrease the incidence of mortality associated with cardiac arrhythmias in children receiving amphotericin B overdoses .
|
adverse effect: mortality -> amphotericin B | adverse effect: cardiac arrhythmias -> amphotericin B
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "cardiac arrhythmias", "relation": "adverse effect", "tail": "amphotericin B"}, {"head": "mortality", "relation": "adverse effect", "tail": "amphotericin B"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Clinicians who manage cachectic patients , particularly those with protracted diarrhoea and/or receiving anti - malarial drugs including mefloquine , should be aware of the risk of severe hypoglycaemia .
|
adverse effect: severe hypoglycaemia -> mefloquine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "severe hypoglycaemia", "relation": "adverse effect", "tail": "mefloquine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
MATERIALS AND METHODS : We present two cases of significant morbidity related to primary and secondary perforation of the bladder following two instillations of epirubicin .
|
adverse effect: primary and secondary perforation of the bladder -> epirubicin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "primary and secondary perforation of the bladder", "relation": "adverse effect", "tail": "epirubicin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Gold nephropathy : tissue analysis by X - ray fluorescent spectroscopy .
|
adverse effect: nephropathy -> Gold
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "nephropathy", "relation": "adverse effect", "tail": "Gold"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Triazolam - induced nocturnal bingeing with amnesia .
|
adverse effect: amnesia -> Triazolam | adverse effect: nocturnal bingeing -> Triazolam
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "amnesia", "relation": "adverse effect", "tail": "Triazolam"}, {"head": "nocturnal bingeing", "relation": "adverse effect", "tail": "Triazolam"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
This case presentation is of a patient who had the clinical appearance of epiglottitis , but actually had an oro - pharyngeal dystonic reaction to prochlorperazine .
|
adverse effect: epiglottitis -> prochlorperazine | adverse effect: oro - pharyngeal dystonic reaction -> prochlorperazine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "epiglottitis", "relation": "adverse effect", "tail": "prochlorperazine"}, {"head": "oro - pharyngeal dystonic reaction", "relation": "adverse effect", "tail": "prochlorperazine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
The probable proarrhythmic action of amiodarone , although rare , is reviewed along with a discussion of the novel use of intravenous magnesium sulfate therapy .
|
adverse effect: proarrhythmic -> amiodarone
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "proarrhythmic", "relation": "adverse effect", "tail": "amiodarone"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Five and one - half years after the diagnosis of myeloma , while in remission on cyclophosphamide therapy , the patient experienced severe abdominal right lower quadrant pain due to a large cecal lymphoma .
|
adverse effect: cecal lymphoma -> cyclophosphamide | adverse effect: abdominal right lower quadrant pain -> cyclophosphamide
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "abdominal right lower quadrant pain", "relation": "adverse effect", "tail": "cyclophosphamide"}, {"head": "cecal lymphoma", "relation": "adverse effect", "tail": "cyclophosphamide"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
OBJECTIVE : To report a case of cutaneous and hematologic toxicity in a patient treated with IL-2 .
|
adverse effect: cutaneous and hematologic toxicity -> IL-2
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "cutaneous and hematologic toxicity", "relation": "adverse effect", "tail": "IL-2"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Sulfasalazine - induced lupus erythematosus .
|
adverse effect: lupus erythematosus -> Sulfasalazine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "lupus erythematosus", "relation": "adverse effect", "tail": "Sulfasalazine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Nephrotic syndrome associated with interferon - beta-1b therapy for multiple sclerosis .
|
adverse effect: Nephrotic syndrome -> interferon - beta-1b
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Nephrotic syndrome", "relation": "adverse effect", "tail": "interferon - beta-1b"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
We report for the first time the development of symptomatic methemoglobinemia after an acute ingestion of divalproex sodium ( Depakote ) , resulting in serum concentrations 10 times greater than the therapeutic range .
|
adverse effect: symptomatic methemoglobinemia -> Depakote | adverse effect: symptomatic methemoglobinemia -> divalproex sodium
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "symptomatic methemoglobinemia", "relation": "adverse effect", "tail": "Depakote"}, {"head": "symptomatic methemoglobinemia", "relation": "adverse effect", "tail": "divalproex sodium"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
CONCLUSIONS : In our reported case , a local hyperproduction of TNF - alpha from macrophages that was induced by the injected insulin could explain the dedifferentiation of the adipocytes of the subcutaneous tissue and the reversion that was induced by the local injection of dexamethasone .
|
adverse effect: hyperproduction of TNF - alpha -> insulin | adverse effect: dedifferentiation of the adipocytes -> insulin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "dedifferentiation of the adipocytes", "relation": "adverse effect", "tail": "insulin"}, {"head": "hyperproduction of TNF - alpha", "relation": "adverse effect", "tail": "insulin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Renal injury due to anastrozole has not been published in the English literature .
|
adverse effect: Renal injury -> anastrozole
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Renal injury", "relation": "adverse effect", "tail": "anastrozole"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Sustained - release procainamide - induced reversible granulocytopenia after myocardial infarction .
|
adverse effect: reversible granulocytopenia -> procainamide
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "reversible granulocytopenia", "relation": "adverse effect", "tail": "procainamide"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
During clarithromycin coadministration , four out of the seven patients developed moderate - to - severe toxic symptoms of carbamazepine , such as drowsiness , dizziness , and ataxia , which resolved within 5 days after clarithromycin discontinuation .
|
adverse effect: drowsiness -> carbamazepine | adverse effect: ataxia -> clarithromycin | adverse effect: dizziness -> carbamazepine | adverse effect: dizziness -> clarithromycin | adverse effect: ataxia -> carbamazepine | adverse effect: toxic symptoms -> clarithromycin | adverse effect: toxic symptoms -> carbamazepine | adverse effect: drowsiness -> clarithromycin
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "ataxia", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "ataxia", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "dizziness", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "dizziness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "clarithromycin"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
However , cyclosporine dependency is associated with the risk of nephrotoxicity .
|
adverse effect: nephrotoxicity -> cyclosporine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "nephrotoxicity", "relation": "adverse effect", "tail": "cyclosporine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
We experienced a case of chronic renal failure in a patient suffering from acute hemorrhagic gastritis associated with AZ intoxication .
|
adverse effect: AZ intoxication -> AZ | adverse effect: acute hemorrhagic gastritis -> AZ
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "acute hemorrhagic gastritis", "relation": "adverse effect", "tail": "AZ"}, {"head": "AZ intoxication", "relation": "adverse effect", "tail": "AZ"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
We now report the first known cancer patient who developed life - threatening complications after treatment with topical 5-FU and was shown subsequently to have profound DPD deficiency .
|
adverse effect: life - threatening complications -> 5-FU
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "life - threatening complications", "relation": "adverse effect", "tail": "5-FU"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
To develop information on the relative rarity or frequency of neurologic worsening with the initiation of penicillamine therapy , we conducted a retrospective survey of 25 additional patients with Wilson 's disease who met the criteria of presenting with neurologic disease and having been treated with penicillamine .
|
adverse effect: neurologic disease -> penicillamine | adverse effect: neurologic worsening -> penicillamine
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "neurologic disease", "relation": "adverse effect", "tail": "penicillamine"}, {"head": "neurologic worsening", "relation": "adverse effect", "tail": "penicillamine"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
RE
|
ADE_corpus_sample_15000
|
train
|
Extract relationships between entities in the text. Format each relationship as 'relation_type: head_entity -> tail_entity' separated by '|'. If no valid relationships exist, return 'None'.
|
Cephalosporins are most likely associated with Vitamin K deficiency .
|
adverse effect: Vitamin K deficiency -> Cephalosporins
|
adverse effect, country capital, members, used for, developer, company industry
|
NYT11: country capital; SciERC_sample_10000: used for; kbp37: members; New-York-Times-RE: company industry; fewrel_4: developer
|
{"relations": [{"head": "Vitamin K deficiency", "relation": "adverse effect", "tail": "Cephalosporins"}]}
|
You are an expert in Relation Extraction.
Your task is to extract relationships between entities in the given text.
Follow these guidelines:
1. Extract ONLY relations of the types specified in the schema
2. Both head and tail entities must be explicitly mentioned in the text
3. Format: 'relation_type: head_entity -> tail_entity' separated by '|'
4. If no relations are found, return 'None'
5. Determine correct directionality (head -> tail) based on the relation semantics
6. Focus on direct, explicit relationships rather than implied or inferred ones
7. Use exact entity text as it appears in the content
Examples show proper entity pairing and direction identification.
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
### Example 3:
- Schema: component whole, content container, entity destination, children, members, member collection, place of birth, instrument agency, product producer, cause effect, message topic, winner, entity origin, na, alternate names
- Content: he has built a formidable reputation writing powerful dramas for the stage and screen , based on real events or socially vital issues .
- Output: None
|
### Example 1:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
### Example 2:
- Schema: administrative division of country, sports discipline competed in, work for, company founded place, live in, company, country of administrative divisions, kill, father, organization based in, located in, sports team location of teams, operator
- Content: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
- Output: Live in: Reagan -> America
|
### Example:
- Schema: hyponym of, used for, conjunction, ethnicity, evaluate for, feature of, located on terrain feature, compare, part of
- Content: Amorph recognizes NE items in two stages : dictionary lookup and rule application
- Output: used for: Amorph -> NE items | part of: dictionary lookup -> Amorph | conjunction: dictionary lookup -> rule application | part of: rule application -> Amorph
|
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