Triple

T20603767
Position Surface form Disambiguated ID Type / Status
Subject Wagon Train E506248 entity
Predicate creator P184 FINISHED
Object Howard Christie 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: Howard Christie | Statement: [Wagon Train, creator, Howard Christie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Christie
Context triple: [Wagon Train, creator, Howard Christie]
  • A. Howard Christie chosen
    Howard Christie was a mid-20th-century American film producer best known for his work on genre and comedy features, including entries in Abbott and Costello’s film series.
  • B. Howard Stevenson
    Howard Stevenson is an American entrepreneur, educator, and longtime Harvard Business School professor known for his influential work on entrepreneurship and venture capital.
  • C. Richard Hiscott
    Richard Hiscott is an editor known for his work on the television series "Willow."
  • D. Richard Bristow
    Richard Bristow was a 16th-century English Catholic scholar and theologian who contributed to the development and annotation of the Douay–Rheims Bible.
  • E. Howard Douglas
    Howard Douglas was a 19th-century British Army general, colonial administrator, and military writer who held several prominent imperial posts.
  • 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_69e0b4bb2b4081908fa4a72444120f35 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa22663881909a8d4644e1c48dc2 completed April 20, 2026, 10:35 p.m.
Created at: April 16, 2026, 11:41 a.m.