Triple

T22452122
Position Surface form Disambiguated ID Type / Status
Subject Nigel Sears E555018 entity
Predicate relative P37 FINISHED
Object Andy Murray 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: Andy Murray | Statement: [Nigel Sears, relative, Andy Murray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andy Murray
Context triple: [Nigel Sears, relative, Andy Murray]
  • A. Andy Murray chosen
    Andy Murray is a Scottish professional tennis player and multiple Grand Slam champion who has been one of Britain’s most successful and prominent sports figures in the modern era.
  • B. Tom Murray
    Tom Murray is a music supervisor known for overseeing and coordinating the musical elements of film and television projects.
  • C. Tom Murray
    Tom Murray was an American character actor of the silent film era, known for his supporting roles in early Hollywood productions.
  • D. Thomas George Roddick
    Thomas George Roddick was a prominent Canadian surgeon, medical reformer, and politician known for helping to establish standardized medical licensing in Canada.
  • E. Greg Rusedski
    Greg Rusedski is a former British-Canadian professional tennis player best known for his powerful left-handed serve and reaching the 1997 US Open final.
  • 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b4c63e88190aeedc326599edd18 completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:48 p.m.