Triple

T12138921
Position Surface form Disambiguated ID Type / Status
Subject Cobb E289132 entity
Predicate title P38 FINISHED
Object Cobb E258349 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: Cobb | Statement: [Cobb, title, Cobb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cobb
Context triple: [Cobb, title, Cobb]
  • A. Cobb chosen
    Cobb is the skilled professional thief and extractor portrayed by Leonardo DiCaprio in Christopher Nolan’s science-fiction film "Inception."
  • B. Cobb
    Cobb is a biographical sports drama film about legendary baseball player Ty Cobb, written and directed by Ron Shelton.
  • C. Cobb
    Cobb is a surname most notably associated with John B. Cobb Jr., an American theologian known for his work in process theology and ecological ethics.
  • D. Ezekiel Cobb
    Ezekiel Cobb is the naive small-town protagonist of the 1912 novel "The Cat's-Paw," whose unwitting involvement in big-city politics drives the story's satirical plot.
  • E. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158eef48819083bdce283a363414 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f690ae408190966bb4fe8feaa7d2 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.