Triple

T6635405
Position Surface form Disambiguated ID Type / Status
Subject In the French Style E150435 entity
Predicate hasCastMember P2308 FINISHED
Object Philippe Forquet E689691 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: Philippe Forquet | Statement: [In the French Style, hasCastMember, Philippe Forquet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippe Forquet
Context triple: [In the French Style, hasCastMember, Philippe Forquet]
  • A. Philippe Forquet chosen
    Philippe Forquet was a French actor and 1960s heartthrob best known for his romantic lead roles in films that paired him with prominent international actresses.
  • B. Frédéric Bricout
    Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
  • C. Philippe Martinaud
    Philippe Martinaud is a lighting designer known for creating the illumination scheme of Tbilisi’s iconic Bridge of Peace.
  • D. François Lecointre
    François Lecointre is a French Army general who served as France’s Chief of the Defence Staff.
  • E. Frédéric Arnault
    Frédéric Arnault is a French business executive known for his leadership roles within the LVMH luxury group, particularly in its watch division.
  • 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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afcc1c9c819087fcde19a5d49fd2 completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91152b4548190a0749cbd3e26cf9e completed March 29, 2026, 11:47 a.m.
Created at: March 27, 2026, 1:59 p.m.