Triple

T1856460
Position Surface form Disambiguated ID Type / Status
Subject Bayonne E41714 entity
Predicate river P165 FINISHED
Object Adour E279030 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: Adour | Statement: [Bayonne, river, Adour]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adour
Context triple: [Bayonne, river, Adour]
  • A. Adour chosen
    Adour is a major river in southwestern France that flows from the Pyrenees to the Atlantic Ocean, passing through cities such as Tarbes and Bayonne.
  • B. Garonne
    The Garonne is a major river in southwestern Europe that flows from the Spanish Pyrenees through cities like Toulouse and Bordeaux before reaching the Atlantic Ocean via the Gironde estuary.
  • C. Aude River
    The Aude River is a major river in southern France that flows through the Occitanie region before emptying into the Mediterranean Sea.
  • D. Allier River
    The Allier River is a major river in central France, known for its largely unspoiled natural course and as a tributary of the Loire.
  • E. Hérault River
    The Hérault River is a 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 (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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb07e5ed48190a7b8858e2b355109 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69af8336f98c8190949c0145d2d31a8f completed March 10, 2026, 2:34 a.m.
Created at: March 4, 2026, 7:33 p.m.