Triple

T621850
Position Surface form Disambiguated ID Type / Status
Subject Bill Murray E14530 entity
Predicate familyName P18 FINISHED
Object Murray E33747 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: Murray | Statement: [Bill Murray, familyName, Murray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murray
Context triple: [Bill Murray, familyName, Murray]
  • A. Murray chosen
    Murray is a masculine given name of Scottish origin that has been borne by various notable figures, including physicist Murray Gell-Mann.
  • B. Murray Sueter
    Murray Sueter was a pioneering British naval officer and aviation advocate who played a key role in the early development of naval air power in the United Kingdom.
  • C. Matthew Taylor
    Matthew Taylor is a British political strategist and policy expert best known for serving as Chief Executive of the Royal Society for the encouragement of Arts, Manufactures and Commerce (RSA) and as a former head of the Number 10 Policy Unit under Prime Minister Tony Blair.
  • D. Frick
    Frick is a surname most prominently associated with American industrialist and art patron Henry Clay Frick.
  • E. Murray Burnett
    Murray Burnett was an American playwright best known for co-writing the stage play that inspired the classic film "Casablanca."
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e402d9c8190936896e3ebb6edc5 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a563cab73c819082b51d64d249143b completed March 2, 2026, 10:17 a.m.
Created at: March 1, 2026, 7:35 p.m.