Triple

T12224969
Position Surface form Disambiguated ID Type / Status
Subject The Sword of Ali Baba E291324 entity
Predicate castMember P1668 FINISHED
Object Peter Whitney E319658 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: Peter Whitney | Statement: [The Sword of Ali Baba, castMember, Peter Whitney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Whitney
Context triple: [The Sword of Ali Baba, castMember, Peter Whitney]
  • A. Peter Whitney chosen
    Peter Whitney was an American character actor known for his burly physique and frequent roles as villains or tough guys in film and television from the 1940s through the 1970s.
  • B. Robert Whitworth
    Robert Whitworth was an 18th-century British civil engineer known for his work on major canal projects during the early development of the UK’s inland waterway network.
  • C. John Watts
    John Watts was an 18th-century London printer and publisher known for producing notable literary and theatrical works.
  • D. John Whiteaker
    John Whiteaker was an American politician who became the first governor of the U.S. state of Oregon after it achieved statehood.
  • E. Edward Milford
    Edward Milford was a senior Australian Army officer and World War II commander who played a key leadership role in the Pacific theatre.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca11f788190bad2efb6c83ffccb completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e5c1c988190a80917dfe782a6b6 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:51 p.m.