Triple

T13512340
Position Surface form Disambiguated ID Type / Status
Subject Carnival Films E322669 entity
Predicate produced P490 FINISHED
Object Traffik E693323 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: Traffik | Statement: [Carnival Films, produced, Traffik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Traffik
Context triple: [Carnival Films, produced, Traffik]
  • A. Traffik
    Traffik is a 2018 American thriller film in which Paula Patton stars as a woman whose romantic getaway turns deadly after she and her boyfriend encounter a violent biker gang involved in human trafficking.
  • B. Traffik chosen
    Traffik is a 1989 British television miniseries that explores the international heroin trade and inspired the later American film "Traffic."
  • C. Trafic
    Trafic is a 1971 French comedy film by Jacques Tati that satirically follows the misadventures of a bumbling car designer trying to deliver his innovative vehicle to an auto show.
  • D. El Tráfico
    El Tráfico is the intense Los Angeles derby between LA Galaxy and Los Angeles FC in Major League Soccer, known for its high-scoring matches and passionate fan atmosphere.
  • E. Traficom
    Traficom is Finland’s national authority responsible for regulating and overseeing transport and communications services, infrastructure, and safety.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf86a6208190be8c18f7a0158f23 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75492676c81909602745e2b6436cb completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:44 p.m.