Triple

T10085202
Position Surface form Disambiguated ID Type / Status
Subject BB 7200 E215200 entity
Predicate nickname P55 FINISHED
Object Nez Cassé E768385 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: Nez Cassé | Statement: [BB 7200, nickname, Nez Cassé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nez Cassé
Context triple: [BB 7200, nickname, Nez Cassé]
  • A. Nez Cassé chosen
    Nez Cassé is the popular nickname for a family of French electric locomotives characterized by their distinctive "broken nose" cab design.
  • B. Mistinguett
    Mistinguett was a famous French actress and singer of the early 20th century, celebrated as one of Paris’s most iconic music-hall stars.
  • C. Tous
    Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
  • D. Souletin
    Souletin is a distinct dialect of the Basque language traditionally spoken in the Soule (Zuberoa) region of the French Basque Country.
  • E. Brice
    Brice is a central character in Tyler Perry's film "Temptation: Confessions of a Marriage Counselor," portrayed as the devoted but imperfect husband whose relationship is tested by infidelity and ambition.
  • 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_69ca83a1eed081908b2e9580f2ebeea7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd04609748190987a9364a387fa61 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b68188c48190ac783cdfc072c502 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.