Triple

T21655307
Position Surface form Disambiguated ID Type / Status
Subject A48 motorway E534447 entity
Predicate servesCity P82 FINISHED
Object Grenoble 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: Grenoble | Statement: [A48 motorway, servesCity, Grenoble]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grenoble
Context triple: [A48 motorway, servesCity, 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 (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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef59176b28819092384fc5f8968022 completed April 27, 2026, 12:39 p.m.
Created at: April 16, 2026, 6:36 p.m.