Triple

T717312
Position Surface form Disambiguated ID Type / Status
Subject Occitanie E14341 entity
Predicate containsCity P294 FINISHED
Object Lavaur E152410 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: Lavaur | Statement: [Occitanie, containsCity, Lavaur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lavaur
Context triple: [Occitanie, containsCity, Lavaur]
  • A. Aurillac
    Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
  • B. Ussel
    Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
  • C. Mazamet chosen
    Mazamet is a town in southern France known historically for its wool and leather industries, situated in the Tarn department within the Occitanie region.
  • D. Gruissan
    Gruissan is a coastal commune in southern France known for its Mediterranean beaches, salt marshes, and traditional stilted chalets.
  • E. Colomiers
    Colomiers is a suburban city in southwestern France, known as part of the Toulouse metropolitan area and for its strong aerospace and industrial sectors.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a577658881909c12951d63d96377 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0132cd6081908d70112213343063 completed March 8, 2026, 4:55 a.m.
Created at: March 1, 2026, 7:37 p.m.