Triple

T543997
Position Surface form Disambiguated ID Type / Status
Subject Maryse Alberti E12691 entity
Predicate collaboratedWith P435 FINISHED
Object Tim Robbins E56260 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: Tim Robbins | Statement: [Maryse Alberti, collaboratedWith, Tim Robbins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tim Robbins
Context triple: [Maryse Alberti, collaboratedWith, Tim Robbins]
  • A. Tim Robbins chosen
    Tim Robbins is an American actor, director, and producer best known for his roles in films such as The Shawshank Redemption, Mystic River, and Bull Durham.
  • B. James Woods
    James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
  • C. Matthew Modine
    Matthew Modine is an American actor best known for his roles in films like "Full Metal Jacket" and the series "Stranger Things."
  • D. Ed Harris
    Ed Harris is an American actor and filmmaker known for his intense, authoritative performances in films such as "The Truman Show," "Apollo 13," and "Pollock."
  • E. Morgan Freeman
    Morgan Freeman is an acclaimed American actor and narrator known for his distinctive deep voice and roles in films such as "The Shawshank Redemption," "Driving Miss Daisy," and "Million Dollar Baby."
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a498dea88881908a938fe8f2313bec completed March 1, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5089bce6c8190a5c4f708fb94668b completed March 2, 2026, 3:48 a.m.
Created at: March 1, 2026, 7:32 p.m.