Triple

T11235555
Position Surface form Disambiguated ID Type / Status
Subject Emmanuelle Seigner E265931 entity
Predicate notableCollaboration P8554 FINISHED
Object Frantic E265926 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: Frantic | Statement: [Emmanuelle Seigner, notableCollaboration, Frantic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frantic
Context triple: [Emmanuelle Seigner, notableCollaboration, Frantic]
  • A. Frantic chosen
    Frantic is a 1988 neo-noir thriller film directed by Roman Polanski, starring Harrison Ford as an American doctor searching for his missing wife in Paris.
  • B. Frenzy
    "Frenzy" is a popular Nigerian Afropop song by artist D'Prince, known for its energetic beat and club-friendly vibe.
  • C. Frenzy
    Frenzy is a 1972 British thriller film directed by Alfred Hitchcock, known for its dark humor and disturbing portrayal of a serial killer in London.
  • D. Frenesi
    "Frenesi" is a popular 1940 jazz and big band standard closely associated with clarinetist and bandleader Artie Shaw.
  • E. Rapid Fire
    Rapid Fire is a 1992 American action film starring Brandon Lee as a college student who becomes entangled in a deadly conflict between drug lords and federal agents.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e904cf888190826fc964f76b5cb2 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc5bcff08190830d09c9aa0187b2 completed April 19, 2026, 12:36 p.m.
Created at: April 8, 2026, 9:30 p.m.