Triple

T9015710
Position Surface form Disambiguated ID Type / Status
Subject Tuck Everlasting E215587 entity
Predicate starredActor P5563 FINISHED
Object William Hurt E222168 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: William Hurt | Statement: [Tuck Everlasting, starredActor, William Hurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Hurt
Context triple: [Tuck Everlasting, starredActor, William Hurt]
  • A. William Hurt chosen
    William Hurt was an acclaimed American actor known for his intense, introspective performances in films such as "Kiss of the Spider Woman," "Broadcast News," and "The Big Chill."
  • B. Matthew Modine
    Matthew Modine is an American actor best known for his roles in films like "Full Metal Jacket" and the series "Stranger Things."
  • C. Ned Beatty
    Ned Beatty was an acclaimed American character actor known for his powerful supporting roles in films such as "Deliverance," "Network," and "Superman."
  • D. James Remar
    James Remar is an American character actor known for his intense and often villainous roles in film and television, including notable performances in projects like "Dexter," "The Warriors," and "48 Hrs."
  • E. Michael Douglas
    Michael Douglas is an acclaimed American actor and producer known for films like "Wall Street" and "Fatal Attraction," who has also been recognized for his humanitarian and peace-promoting work.
  • 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_69ca83a38aa88190bf1bb80c4548b5e2 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69fc0e4c819080b60456375f94cd completed April 1, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d02fc332c881908847e70bee4695af completed April 3, 2026, 9:23 p.m.
Created at: March 30, 2026, 7:06 p.m.