Triple

T2107641
Position Surface form Disambiguated ID Type / Status
Subject Nouvelle-Aquitaine E42430 entity
Predicate contains P35 FINISHED
Object Périgueux E103705 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: Périgueux | Statement: [Nouvelle-Aquitaine, contains, Périgueux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Périgueux
Context triple: [Nouvelle-Aquitaine, contains, Périgueux]
  • A. Montluçon
    Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
  • B. Cahors
    Cahors is a historic town in southwestern France renowned for its medieval architecture, including the fortified Valentré Bridge, and its surrounding Malbec wine-producing vineyards.
  • C. Guéret
    Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
  • D. Figeac
    Figeac is a historic town in southwestern France known for its medieval architecture and as the birthplace of Jean-François Champollion, who deciphered Egyptian hieroglyphs.
  • E. Ribérac chosen
    Ribérac is a small historic town in southwestern France’s Dordogne department, known for its traditional markets and rural charm.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbadf12b88190acc513d8512777b2 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae306e040081909334f2a70036c26e completed March 9, 2026, 2:29 a.m.
Created at: March 4, 2026, 7:43 p.m.