Triple

T18724535
Position Surface form Disambiguated ID Type / Status
Subject Nick Ryder E457862 entity
Predicate collaboratesWith P37 FINISHED
Object Tom B. Brown NE NERFINISHED

How this triple was built (2 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: Tom B. Brown | Statement: [Nick Ryder, collaboratesWith, Tom B. Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom B. Brown
Context triple: [Nick Ryder, collaboratesWith, Tom B. Brown]
  • A. Tom B. Brown chosen
    Tom B. Brown is a machine learning researcher known for leading work on large-scale language models, including the influential GPT-3 paper "Language Models are Few-Shot Learners."
  • B. Thomas J. Brown
    Thomas J. Brown is an American Episcopal bishop who serves as the diocesan leader of the Episcopal Diocese of Maine.
  • C. J. Douglas Brown
    J. Douglas Brown was an American economist and academic who played a key role in shaping U.S. Social Security policy during the New Deal era.
  • D. Len Brown
    Len Brown is a New Zealand politician who became the inaugural mayor of the amalgamated Auckland "super city," serving from 2010 to 2016.
  • E. David H. Brown
    David H. Brown was one of the defendants tried alongside Dr. Ossian Sweet in the landmark 1925 Detroit case involving racial tensions, self-defense, and housing segregation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d393ba9c8190a8b03b04ddbb0a09 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d72d2c4819080b0d31860976b5e completed April 20, 2026, 12:04 a.m.
Created at: April 10, 2026, 11:50 a.m.