Triple

T14676724
Position Surface form Disambiguated ID Type / Status
Subject Arve E344664 entity
Predicate hasMajorTributary P415 FINISHED
Object Giffre E343874 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: Giffre | Statement: [Arve, hasMajorTributary, Giffre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Giffre
Context triple: [Arve, hasMajorTributary, Giffre]
  • A. Vidourle
    Vidourle is a river in southern France that flows through the Gard department before emptying into the Mediterranean Sea.
  • B. Alès
    Alès is a historic industrial town in southern France, located at the foot of the Cévennes mountains.
  • C. Giffre valley chosen
    Giffre valley is a scenic alpine valley in the French Alps known for its dramatic limestone cliffs, waterfalls, and traditional mountain villages.
  • D. Ardiège
    Ardiège is a small commune in southwestern France, located in the Haute-Garonne department within the Occitanie region.
  • E. Val d’Ayas
    Val d’Ayas is a scenic alpine valley in Italy’s Aosta Valley region, known for its traditional mountain villages, hiking trails, and access to the Monte Rosa ski area.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb567c2b88190a9639e61b6fba7df completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cde041081908ae2f2c75a9d5eb2 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:27 a.m.