Triple

T10709095
Position Surface form Disambiguated ID Type / Status
Subject Vienne River E252485 entity
Predicate mouthLocation P417 FINISHED
Object Candes-Saint-Martin E298110 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: Candes-Saint-Martin | Statement: [Vienne River, mouthLocation, Candes-Saint-Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Candes-Saint-Martin
Context triple: [Vienne River, mouthLocation, Candes-Saint-Martin]
  • A. Candes-Saint-Martin chosen
    Candes-Saint-Martin is a picturesque historic village in central France, known for its medieval architecture and scenic location at the confluence of the Vienne and Loire rivers.
  • B. Lasserre
    Lasserre is a small rural commune in southwestern France known for being the later-life home of the influential mathematician Alexander Grothendieck.
  • C. Courcier
    Courcier was a French publishing house known for issuing important mathematical and scientific works in the early 19th century.
  • D. Desnos
    Desnos is the surname of Robert Desnos, a notable French surrealist poet and member of the Resistance during World War II.
  • E. Cazeneuve
    Cazeneuve is a French surname most notably borne by Bernard Cazeneuve, a prominent French politician and former Prime Minister of France.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe5063bc8190ba12fd68a59c9a03 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbad1ac3948190a97ab52fa9d962ad completed April 12, 2026, 2:32 p.m.
Created at: April 8, 2026, 9:13 p.m.