Triple

T1755467
Position Surface form Disambiguated ID Type / Status
Subject Dianne Wiest E38535 entity
Predicate hasWorkedWith P9615 FINISHED
Object Mike Nichols E51656 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: Mike Nichols | Statement: [Dianne Wiest, hasWorkedWith, Mike Nichols]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Nichols
Context triple: [Dianne Wiest, hasWorkedWith, Mike Nichols]
  • A. Mike Nichols chosen
    Mike Nichols was an acclaimed American film and theater director known for influential works like "The Graduate" and his sharp, character-driven storytelling that helped define a generation of cinema.
  • B. Sydney Pollack
    Sydney Pollack was an American film director, producer, and actor known for acclaimed movies such as "Out of Africa," "Tootsie," and "The Firm."
  • C. Sidney Lumet
    Sidney Lumet was an acclaimed American film director known for socially conscious, character-driven dramas such as "12 Angry Men," "Serpico," and "Dog Day Afternoon."
  • D. Alan J. Pakula
    Alan J. Pakula was an American film director, producer, and screenwriter best known for his politically charged thrillers and character-driven dramas of the 1970s and 1980s.
  • E. Blake Edwards
    Blake Edwards was an American filmmaker best known for his stylish comedies and classics like the Pink Panther series and Breakfast at Tiffany’s.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa643b623081908064be75758ec5de completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0ea4cc08190b47d81a54c294a9a completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.