Triple

T5063254
Position Surface form Disambiguated ID Type / Status
Subject Lot River E114077 entity
Predicate flowsThrough P225 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 River, flowsThrough, Cahors]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cahors
Context triple: [Lot River, flowsThrough, 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_69bd443c0c8c81908663b77afb28e165 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7475be3c819085cde8ec544c407e completed March 20, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b069d3fc8190bac9d178a571b72d completed March 23, 2026, 3:15 a.m.
Created at: March 20, 2026, 1:38 p.m.