Triple

T19508446
Position Surface form Disambiguated ID Type / Status
Subject Al Alcorn E488086 entity
Predicate collaboratedWith P435 FINISHED
Object Ted Dabney 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: Ted Dabney | Statement: [Al Alcorn, collaboratedWith, Ted Dabney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ted Dabney
Context triple: [Al Alcorn, collaboratedWith, Ted Dabney]
  • A. Ted Dabney chosen
    Ted Dabney was an American electrical engineer and co-founder of Atari who played a key role in the early development of the video game industry.
  • B. Arthur Dorman
    Arthur Dorman was a British industrialist best known as a co-founder of the major steel and engineering firm Dorman Long and Co Ltd, which played a significant role in bridge building and heavy industry.
  • C. Arthur E. Bryson Jr.
    Arthur E. Bryson Jr. is a pioneering control theorist and aerospace engineer often regarded as a founder of modern optimal control theory.
  • D. Douglas Seale
    Douglas Seale was a British actor and voice artist known for his character roles in film, television, and animation, including work with Disney.
  • E. Robert Clohessy
    Robert Clohessy is an American actor best known for his recurring roles on television dramas, including his portrayal of police officers on series such as Blue Bloods and Oz.
  • 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6351426448190aec1ee26c09faa24 completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.