Triple

T12167320
Position Surface form Disambiguated ID Type / Status
Subject Couze Chambon E289866 entity
Predicate hasName P744 FINISHED
Object Couze Chambon E289866 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: Couze Chambon | Statement: [Couze Chambon, hasName, Couze Chambon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Couze Chambon
Context triple: [Couze Chambon, hasName, Couze Chambon]
  • A. Couze Chambon chosen
    Couze Chambon is a river in central France that flows through the Monts Dore volcanic massif in the Auvergne region.
  • B. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • C. Châtel-Censoir
    Châtel-Censoir is a small commune in the Yonne department of central France, known for its picturesque setting along the Canal du Nivernais and its historic village character.
  • D. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • E. Châteaurenard
    Châteaurenard is a commune in southern France known for its agricultural production and Provençal heritage, located near Avignon in the Bouches-du-Rhône department.
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915d85c088190a74fb7590877659b completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a84236c8190baa383c950d2bd62 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:50 p.m.