Triple

T3075705
Position Surface form Disambiguated ID Type / Status
Subject Drew Bagnell E64130 entity
Predicate name P16 FINISHED
Object Drew Bagnell E64130 NE FINISHED

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: Drew Bagnell | Statement: [Drew Bagnell, name, Drew Bagnell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drew Bagnell
Context triple: [Drew Bagnell, name, Drew Bagnell]
  • A. Drew Bagnell chosen
    Drew Bagnell is a roboticist and machine learning researcher known for his work in autonomous systems and his role as a co-founder and chief scientist at Aurora Innovation.
  • B. Drew Ferguson
    Drew Ferguson is an American Republican politician and dentist serving as a U.S. Representative from Georgia.
  • C. Drew Hansen
    Drew Hansen is an American lawyer, author, and Democratic politician who has served in the Washington State Legislature.
  • D. Brant Daugherty
    Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
  • E. Nathan Maloney
    Nathan Maloney is a central teenage character in the British TV drama "Queer as Folk," known for exploring his sexuality and identity within Manchester’s gay scene.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad857a8aec8190bfdfd9c14554ac5a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada150d8e08190bde5f68e800e8feb completed March 8, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ded6588819093abd0c0c6158579 completed March 12, 2026, 9:57 a.m.
Created at: March 8, 2026, 3:02 p.m.