Triple

T14414933
Position Surface form Disambiguated ID Type / Status
Subject Daniel Brière E357424 entity
Predicate familyName P18 FINISHED
Object Brière E357424 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: Brière | Statement: [Daniel Brière, familyName, Brière]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brière
Context triple: [Daniel Brière, familyName, Brière]
  • A. Brière chosen
    Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
  • B. Ferrière
    Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
  • C. Vaujours
    Vaujours is a small suburban commune in the northeastern outskirts of Paris, France.
  • D. Viry-Châtillon
    Viry-Châtillon is a suburban commune in the southern outskirts of Paris, France, known for its residential character and location along the Seine River in the Essonne department.
  • E. Montferrand
    Montferrand is a historic French town, now part of Clermont-Ferrand, known for its medieval heritage and former status as a separate commune in the Auvergne region.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90cc99208190a2313b1acfb5d802 completed April 14, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff13322c548190bac21db2bfa56ee9 completed May 9, 2026, 10:57 a.m.
Created at: April 10, 2026, 1:17 a.m.