Triple

T309218
Position Surface form Disambiguated ID Type / Status
Subject Matt Damon E6366 entity
Predicate name P16 FINISHED
Object Matt Damon E6366 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: Matt Damon | Statement: [Matt Damon, name, Matt Damon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Damon
Context triple: [Matt Damon, name, Matt Damon]
  • A. Matt Damon chosen
    Matt Damon is an American actor, producer, and screenwriter known for his versatile performances in films such as Good Will Hunting, the Bourne series, and The Martian.
  • B. George Clooney
    George Clooney is an American actor, filmmaker, and activist renowned for his work in film and television as well as his humanitarian and political advocacy.
  • C. Leonardo DiCaprio
    Leonardo DiCaprio is an Academy Award–winning American actor and environmental activist known for his roles in films like Titanic, Inception, and The Revenant, as well as his prominent climate advocacy.
  • D. Guy Pearce
    Guy Pearce is an Australian actor known for his versatile performances in films such as "Memento," "L.A. Confidential," and "The King's Speech."
  • E. Casey Affleck
    Casey Affleck is an American actor and filmmaker known for his understated, emotionally intense performances in films such as "Manchester by the Sea," for which he won the Academy Award for Best Actor.
  • 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_69a2e79230508190b912ecb555aae17e completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea33ba688190b30d285cd7aa0d82 completed Feb. 28, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3b475e91c8190b68b05a8112d35dd completed March 1, 2026, 3:37 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.