Triple

T9303715
Position Surface form Disambiguated ID Type / Status
Subject Matthew Gentzkow E223828 entity
Predicate coAuthor P398 FINISHED
Object Nathan Petek
Nathan Petek is an academic researcher known for coauthoring economics-related work with scholars such as Matthew Gentzkow.
E790062 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nathan Petek | Statement: [Matthew Gentzkow, coAuthor, Nathan Petek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nathan Petek
Context triple: [Matthew Gentzkow, coAuthor, Nathan Petek]
  • A. Nathan Keller
    Nathan Keller is an Israeli mathematician and cryptographer known for his work in discrete mathematics, Boolean functions, and the analysis of cryptographic algorithms.
  • B. Trenton Fisher
    Trenton Fisher is known as the husband of American singer Kate Smith.
  • C. Preston D'Ambrosio
    Preston D'Ambrosio is a fictional character appearing in the film "In Too Deep."
  • D. Alex Tuch
    Alex Tuch is an American professional ice hockey winger in the NHL known for his size, speed, and scoring ability.
  • E. Trent Baalke
    Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nathan Petek
Triple: [Matthew Gentzkow, coAuthor, Nathan Petek]
Generated description
Nathan Petek is an academic researcher known for coauthoring economics-related work with scholars such as Matthew Gentzkow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nathan Petek
Target entity description: Nathan Petek is an academic researcher known for coauthoring economics-related work with scholars such as Matthew Gentzkow.
  • A. Nathan Keller
    Nathan Keller is an Israeli mathematician and cryptographer known for his work in discrete mathematics, Boolean functions, and the analysis of cryptographic algorithms.
  • B. Trenton Fisher
    Trenton Fisher is known as the husband of American singer Kate Smith.
  • C. Preston D'Ambrosio
    Preston D'Ambrosio is a fictional character appearing in the film "In Too Deep."
  • D. Alex Tuch
    Alex Tuch is an American professional ice hockey winger in the NHL known for his size, speed, and scoring ability.
  • E. Trent Baalke
    Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca8424d0f08190831e2e93c6533aeb completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd08d4c5e48190aa8c744a158e5fbb completed April 1, 2026, noon
NED1 Entity disambiguation (via context triple) batch_69d0b26ae3c881909e88f0253e73f0ea completed April 4, 2026, 6:40 a.m.
NEDg Description generation batch_69d0b3ba0bd88190873816ec7e7929a7 completed April 4, 2026, 6:46 a.m.
NED2 Entity disambiguation (via description) batch_69d0b49ec4c88190a48909e7022d7e60 completed April 4, 2026, 6:50 a.m.
Created at: March 30, 2026, 7:36 p.m.