Triple

T7182170
Position Surface form Disambiguated ID Type / Status
Subject Starbucks E167473 entity
Predicate coFounder P2835 FINISHED
Object Gordon Bowker E167473 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: Gordon Bowker | Statement: [Starbucks, coFounder, Gordon Bowker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gordon Bowker
Context triple: [Starbucks, coFounder, Gordon Bowker]
  • A. Gordon Bowker chosen
    Gordon Bowker is an American writer and entrepreneur best known as one of the co-founders of the global coffee company Starbucks.
  • B. Gordon Juckes
    Gordon Juckes was a prominent Canadian ice hockey administrator who played a key role in developing and promoting amateur hockey across Canada.
  • C. Gordon Dawson
    Gordon Dawson is an American screenwriter and producer best known for his collaborations with director Sam Peckinpah on films such as "Bring Me the Head of Alfredo Garcia."
  • D. Gordon Hales
    Gordon Hales was a film editor known for his work on major British and international productions, including Charlie Chaplin’s final film "A Countess from Hong Kong."
  • E. Martin Boddey
    Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8bc25088190a7d7f3ba2461b5e9 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d37cfb8c8190a788dcaa1080fb0b completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:49 p.m.