Triple

T7278505
Position Surface form Disambiguated ID Type / Status
Subject Lot (department) E163090 entity
Predicate prefecture P7509 FINISHED
Object Cahors E171878 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: Cahors | Statement: [Lot (department), prefecture, Cahors]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cahors
Context triple: [Lot (department), prefecture, Cahors]
  • A. Cahors chosen
    Cahors is a historic town in southwestern France renowned for its medieval architecture, including the fortified Valentré Bridge, and its surrounding Malbec wine-producing vineyards.
  • B. Pont-Saint-Esprit
    Pont-Saint-Esprit is a historic commune in southern France, known for its medieval bridge over the Rhône River and its location in the Gard department of the Occitanie region.
  • C. Béziers
    Béziers is a historic city in southern France known for its wine production, ancient Roman heritage, and the famous Feria de Béziers festival.
  • D. Albi
    Albi is a historic city in southern France renowned for its red-brick medieval architecture and the UNESCO-listed Episcopal City centered around Sainte-Cécile Cathedral.
  • E. Montpellier
    Montpellier is a major city in southern France known for its medieval old town, vibrant university life, and proximity to the Mediterranean coast.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb3251808190bd9da71bc183c945 completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c963dc62f88190b2aff49f5cb5fe27 completed March 29, 2026, 5:39 p.m.
Created at: March 27, 2026, 2:59 p.m.