Triple

T2983116
Position Surface form Disambiguated ID Type / Status
Subject Jean-Pierre Marielle E80557 entity
Predicate givenName P17 FINISHED
Object Jean-Pierre E27779 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: Jean-Pierre | Statement: [Jean-Pierre Marielle, givenName, Jean-Pierre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean-Pierre
Context triple: [Jean-Pierre Marielle, givenName, Jean-Pierre]
  • A. Jean-Pierre chosen
    Jean-Pierre is a French given name commonly used as a masculine compound first name.
  • B. Gérard
    Gérard is a French given name, equivalent to the Germanic name Gerhard, commonly used in French-speaking countries.
  • C. Jean-Claude Olivier
    Jean-Claude Olivier is a writer associated with the Juicy brand or publication.
  • D. Gérard Lopez
    Gérard Lopez is a Luxembourgish-Spanish businessman and investor known for owning and leading several European football clubs, including Girondins de Bordeaux and previously Lille OSC.
  • E. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99a1ed44819085ae6d39943db1d9 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b23592a4888190a78fcae60f4971dd completed March 12, 2026, 3:40 a.m.
Created at: March 8, 2026, 2:58 p.m.