Triple

T3761464
Position Surface form Disambiguated ID Type / Status
Subject Corrèze E82169 entity
Predicate contains P35 FINISHED
Object Ussel E104980 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: Ussel | Statement: [Corrèze, contains, Ussel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ussel
Context triple: [Corrèze, contains, Ussel]
  • A. Ussel chosen
    Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
  • B. Aurillac
    Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
  • C. Cauterets
    Cauterets is a spa and ski resort town in the French Pyrenees known for its thermal baths, mountain scenery, and access to popular hiking areas.
  • D. Anduze
    Anduze is a historic town in southern France, known as a gateway to the Cévennes region and for its traditional pottery and scenic setting along the Gardon River.
  • E. Uzès
    Uzès is a historic town in southern France’s Occitanie region, known for its well-preserved medieval architecture and proximity to the Pont du Gard.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc553a08190ba361675901496ed completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb0fc6248190b2f4adf3fd2d73d9 completed March 14, 2026, 6:07 a.m.
Created at: March 8, 2026, 3:35 p.m.