Triple

T12487901
Position Surface form Disambiguated ID Type / Status
Subject Charente E298483 entity
Predicate contains P35 FINISHED
Object Charente River E298483 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: Charente River | Statement: [Charente, contains, Charente River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charente River
Context triple: [Charente, contains, Charente River]
  • A. Vendée River
    The Vendée River is a waterway in western France that flows through the Vendée department and lends its name to the region.
  • B. Charente chosen
    Charente is a department in southwestern France known for its historic towns, cognac production, and scenic river landscapes.
  • C. Dordogne River
    The Dordogne River is a major river in south-central and southwestern France, renowned for its scenic valleys, historic towns, and role in the region’s cultural and natural heritage.
  • D. Charentonne River
    The Charentonne River is a watercourse in northern France that flows through the town of Bernay and contributes to the region’s rural and historical landscape.
  • E. Thouet River
    The Thouet River is a tributary of the Loire in western France, flowing through the Deux-Sèvres department and several historic towns before joining the Loire near Saumur.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de077bc81908b5ff057a1bf2b4f completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a82c2b9c819084ffd933e5b295b9 completed May 3, 2026, 7:55 p.m.
Created at: April 8, 2026, 9:56 p.m.