Triple

T19419695
Position Surface form Disambiguated ID Type / Status
Subject Canigó E485815 entity
Predicate near P350 FINISHED
Object Conflent NE NERFINISHED

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: Conflent | Statement: [Canigó, near, Conflent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Conflent
Context triple: [Canigó, near, Conflent]
  • A. Conflent chosen
    Conflent is a historical region in the eastern Pyrenees, now in southern France, known for its Catalan heritage and strategic mountain valleys.
  • B. Célé River
    The Célé River is a scenic tributary of the Lot in southwestern France, known for flowing through limestone gorges and past prehistoric cave sites such as Pech Merle.
  • C. Gave de Pau River
    The Gave de Pau River is a river in southwestern France that flows through the Pyrenees and the city of Pau before joining the Adour.
  • D. Deûle River
    The Deûle River is a canalised river in northern France that flows through the city of Lille and serves as an important waterway in the region.
  • E. Aude River
    The Aude River is a major river in southern France that flows through the Occitanie region before emptying into the Mediterranean Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63213b6ec8190b89982b554a0f6e7 completed April 20, 2026, 2:02 p.m.
Created at: April 10, 2026, 1:37 p.m.