Triple

T3685632
Position Surface form Disambiguated ID Type / Status
Subject Dordogne E78217 entity
Predicate crossesDepartment P27425 FINISHED
Object Cantal E52560 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: Cantal | Statement: [Dordogne, crossesDepartment, Cantal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cantal
Context triple: [Dordogne, crossesDepartment, Cantal]
  • A. Cantal chosen
    Cantal is a rural department in south-central France known for its volcanic landscapes, pastoral agriculture, and the production of Cantal cheese.
  • B. Osona
    Osona is a historical inland comarca in Catalonia, Spain, known for its rural landscapes, medieval towns, and the city of Vic as its main urban center.
  • C. Louletano
    Louletano is the Portuguese demonym used to refer to people or things originating from the city of Loulé in the Algarve region.
  • D. Bega
    Bega is a rural town in New South Wales, Australia, best known as a major dairy and cheese-producing centre.
  • E. Cigales
    Cigales is a small town in the province of Valladolid, Spain, known historically as a royal residence and for its wine production.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c49b408190bc800bcf9745fe4f completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3bd473c8190b814689f3c76cada completed March 14, 2026, 2:11 a.m.
Created at: March 8, 2026, 3:26 p.m.