Triple

T5649834
Position Surface form Disambiguated ID Type / Status
Subject Michele E124474 entity
Predicate hasFamousBearer P458 FINISHED
Object Michele Mouton E458295 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: Michele Mouton | Statement: [Michele, hasFamousBearer, Michele Mouton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michele Mouton
Context triple: [Michele, hasFamousBearer, Michele Mouton]
  • A. Michele Mouton chosen
    Michele Mouton is a pioneering French rally driver best known as the first woman to win a World Rally Championship event and as a leading competitor in the early 1980s Group B era.
  • B. Charles LeMaire
    Charles LeMaire was an American costume designer renowned for his work in Hollywood’s Golden Age, earning multiple Academy Awards for his contributions to classic films.
  • C. Louis Dombrowski
    Louis Dombrowski is an individual notable enough to be recognized as a prominent bearer of the surname Dombrowski.
  • D. Joseph Mazilier
    Joseph Mazilier was a 19th-century French ballet dancer, choreographer, and ballet master known for creating several major Romantic ballets.
  • E. Michel Macary
    Michel Macary is a French architect best known for co-designing major public venues, including the iconic Stade de France in Paris.
  • 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_69c00825df388190a58742fa9b1aa33d completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022d2ed648190a5152c8668cbda02 completed March 22, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07db3f0448190bfcb66f5af5dbf99 completed March 22, 2026, 11:39 p.m.
Created at: March 22, 2026, 3:42 p.m.