Triple

T6955155
Position Surface form Disambiguated ID Type / Status
Subject Ted (2012 film) E161222 entity
Predicate character P662 FINISHED
Object John Bennett E141761 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: John Bennett | Statement: [Ted (2012 film), character, John Bennett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Bennett
Context triple: [Ted (2012 film), character, John Bennett]
  • A. John Bennett chosen
    John Bennett is the central human protagonist of the comedy film "Ted 2," known for his lifelong friendship with his foul-mouthed, living teddy bear.
  • B. Nicholas Baker
    Nicholas Baker is an alternate name associated with Niels Bohr, the pioneering Danish physicist who made foundational contributions to understanding atomic structure and quantum theory.
  • C. Nicholas Baker
    Nicholas Baker is a relatively uncommon personal name that may refer to multiple individuals across different fields rather than a single widely recognized public figure.
  • D. David Marvin Blake
    David Marvin Blake is an American rapper, DJ, and record producer best known by his stage name DJ Quik, a prominent figure in West Coast hip hop.
  • E. Gene Milford
    Gene Milford was an American film editor known for his work on numerous classic Hollywood films across several decades.
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dace1a94819095311e4288f01784 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7753f1fe08190a734e371db4d1d38 completed March 28, 2026, 6:29 a.m.
Created at: March 27, 2026, 2:29 p.m.