Tom B. Brown et al.
E102297
Tom B. Brown et al. are the research team behind the influential GPT-3 language model paper that significantly advanced large-scale neural language modeling.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Tom B. Brown et al. canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T871359 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: Tom B. Brown et al. Context triple: [GPT-3, paperAuthors, Tom B. Brown et al.]
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A.
Kivett & Myers
Kivett & Myers was an American architectural firm best known for designing major sports venues, including Arrowhead Stadium in Kansas City.
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B.
Jones, Skelton & Hochuli
Jones, Skelton & Hochuli is a Phoenix-based civil litigation and insurance defense law firm co-founded by prominent attorney and NFL referee Ed Hochuli.
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C.
Clark/Hunt/Smoot
Clark/Hunt/Smoot is a construction joint venture known for serving as the primary builder on major projects, including large sports venues in the United States.
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D.
Zantzinger, Borie and Medary
Zantzinger, Borie and Medary was a prominent early 20th-century American architectural firm known for its grand Beaux-Arts and classical revival designs.
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E.
Graham, Anderson, Probst & White
Graham, Anderson, Probst & White was a prominent early 20th-century American architectural firm known for designing major Beaux-Arts and classical revival landmarks, particularly in Chicago.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Tom B. Brown et al. Target entity description: Tom B. Brown et al. are the research team behind the influential GPT-3 language model paper that significantly advanced large-scale neural language modeling.
-
A.
Kivett & Myers
Kivett & Myers was an American architectural firm best known for designing major sports venues, including Arrowhead Stadium in Kansas City.
-
B.
Jones, Skelton & Hochuli
Jones, Skelton & Hochuli is a Phoenix-based civil litigation and insurance defense law firm co-founded by prominent attorney and NFL referee Ed Hochuli.
-
C.
Clark/Hunt/Smoot
Clark/Hunt/Smoot is a construction joint venture known for serving as the primary builder on major projects, including large sports venues in the United States.
-
D.
Zantzinger, Borie and Medary
Zantzinger, Borie and Medary was a prominent early 20th-century American architectural firm known for its grand Beaux-Arts and classical revival designs.
-
E.
Graham, Anderson, Probst & White
Graham, Anderson, Probst & White was a prominent early 20th-century American architectural firm known for designing major Beaux-Arts and classical revival landmarks, particularly in Chicago.
- F. None of above. chosen
Statements (86)
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Subject: Tom B. Brown et al. Description of subject: Tom B. Brown et al. are the research team behind the influential GPT-3 language model paper that significantly advanced large-scale neural language modeling.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.