Triple

T4718802
Position Surface form Disambiguated ID Type / Status
Subject Aveyron E104712 entity
Predicate bordersDepartment P224 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: [Aveyron, bordersDepartment, Cantal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cantal
Context triple: [Aveyron, bordersDepartment, 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. Vernazobre
    Vernazobre is a river in southern France that serves as a tributary of the Orb.
  • C. 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.
  • D. Louletano
    Louletano is the Portuguese demonym used to refer to people or things originating from the city of Loulé in the Algarve region.
  • E. Bega Valley
    Bega Valley is a coastal region in southeastern New South Wales, Australia, known for its dairy industry, scenic beaches, and rural landscapes.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd642779a08190b01e588d515cf498 completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be108bc0048190aeea8674f75105e5 completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:18 p.m.