Triple

T14368052
Position Surface form Disambiguated ID Type / Status
Subject Critérium du Dauphiné Libéré 1966 E356285 entity
Predicate finishLocation P2684 FINISHED
Object Grenoble E91863 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: Grenoble | Statement: [Critérium du Dauphiné Libéré 1966, finishLocation, Grenoble]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grenoble
Context triple: [Critérium du Dauphiné Libéré 1966, finishLocation, Grenoble]
  • A. Grenoble chosen
    Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
  • B. Aix-les-Bains
    Aix-les-Bains is a French spa and resort town in the Savoie department, renowned for its thermal baths and lakeside setting on the edge of the Alps.
  • C. Chambéry
    Chambéry is a historic city in southeastern France that served as the political and cultural center of the former Duchy of Savoy.
  • D. Briançon
    Briançon is a fortified alpine town in southeastern France, known as one of the highest cities in Europe and a key historical stronghold near the Italian border.
  • E. Clermont-Ferrand
    Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8faf00e8819087d7100e9d8c1877 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe387f28688190b9d20f1e2bbc0ddc completed May 8, 2026, 7:24 p.m.
Created at: April 10, 2026, 1:15 a.m.