Triple

T7630994
Position Surface form Disambiguated ID Type / Status
Subject The Client E172757 entity
Predicate productionCompany P490 FINISHED
Object Alcor Films E542157 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: Alcor Films | Statement: [The Client, productionCompany, Alcor Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alcor Films
Context triple: [The Client, productionCompany, Alcor Films]
  • A. Alcor Films chosen
    Alcor Films is a film production company best known for producing the 1994 legal thriller "The Client."
  • B. Rastar Films
    Rastar Films was an American film production company known for producing a range of notable Hollywood films from the 1960s through the 1980s.
  • C. Pantelion Films
    Pantelion Films is a film production and distribution company known for specializing in Latino-focused and Spanish-language movies, formed as a joint venture between Lionsgate and Televisa.
  • D. Vistar Films
    Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
  • E. Alliance Films
    Alliance Films was a major Canadian film distribution and production company known for releasing a wide range of independent and international movies in Canada and other markets.
  • 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_69c699517e348190bd3348b6889200f2 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa85c57c8190acfd33e0c890c2f9 completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89ab967108190bffea7676c44232b completed March 29, 2026, 3:21 a.m.
Created at: March 27, 2026, 3:56 p.m.