Triple

T22093119
Position Surface form Disambiguated ID Type / Status
Subject Orphan (2009 film) E545957 entity
Predicate mainCharacter P1183 FINISHED
Object Daniel Coleman NE NERFINISHED

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: Daniel Coleman | Statement: [Orphan (2009 film), mainCharacter, Daniel Coleman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Coleman
Context triple: [Orphan (2009 film), mainCharacter, Daniel Coleman]
  • A. Wesley Wyndam-Pryce
    Wesley Wyndam-Pryce is a former Watcher turned morally conflicted demon hunter and scholar, best known as a central character on the TV series "Angel."
  • B. Sam Kendricks
    Sam Kendricks is an American pole vaulter and Olympic medalist known for his multiple World Championship titles and national records in the event.
  • C. Roger Black
    Roger Black is an American comedian, writer, and animator best known for co-creating the adult animated television series Brickleberry.
  • D. Sean Canning
    Sean Canning is a notable individual who shares the Canning surname, recognized for achievements that distinguish him among others with that name.
  • E. Aaron Lohr chosen
    Aaron Lohr is an American actor and singer known for his roles in films like "The Mighty Ducks" series and "Newsies," as well as for his work in musical theatre.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e6b1d881909bf0f4a52199354c completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.