Triple

T16100492
Position Surface form Disambiguated ID Type / Status
Subject William Loose E390604 entity
Predicate name P16 FINISHED
Object William Loose E390604 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: William Loose | Statement: [William Loose, name, William Loose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Loose
Context triple: [William Loose, name, William Loose]
  • A. William Loose chosen
    William Loose was an American composer and arranger best known for his prolific work on film and television scores, particularly in mid-20th-century Hollywood.
  • B. William Gillespie
    William Gillespie was a Scottish-born character actor of the silent and early sound film era, known for his supporting roles in numerous comedies, including those produced by Hal Roach.
  • C. Peter Paul Marshall
    Peter Paul Marshall was a 19th-century British painter and civil engineer best known as one of the founding partners of the Arts and Crafts firm Morris, Marshall, Faulkner & Co.
  • D. Bill Brennan
    Bill Brennan was an early 20th-century American baseball umpire who worked in both the major leagues and prominent postseason series.
  • E. Jeff Buchanan
    Jeff Buchanan is a professional editor, likely working in publishing or media, known for collaborating on written content such as articles or manuscripts.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6756948190a7f5ecb375e59701 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff29f9f2881909b96860ee23d8ada completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5 a.m.