Triple

T12521807
Position Surface form Disambiguated ID Type / Status
Subject Puy Mary viewpoint E299335 entity
Predicate administrativeDepartment P14872 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: [Puy Mary viewpoint, administrativeDepartment, Cantal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cantal
Context triple: [Puy Mary viewpoint, administrativeDepartment, 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. Monforte d’Alba
    Monforte d’Alba is a renowned wine-producing village in Italy’s Piedmont region, celebrated for its high-quality Barolo wines and picturesque Langhe hillside landscapes.
  • C. Vernazobre
    Vernazobre is a river in southern France that serves as a tributary of the Orb.
  • D. Fassano
    Fassano is an alternative name for the village of Fodom in the Veneto region of northern Italy.
  • E. 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.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545b2b2481909049a490c97678f2 completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bbf43e08190ae79f92ed5882ce2 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.