Triple

T17703420
Position Surface form Disambiguated ID Type / Status
Subject Count of Osona E441366 entity
Predicate hasRegion P285 FINISHED
Object Osona NE NERFINISHED

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: Osona | Statement: [Count of Osona, hasRegion, Osona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Osona
Context triple: [Count of Osona, hasRegion, Osona]
  • A. Osona chosen
    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.
  • B. Resega
    Resega is the former name of the ice hockey arena in Lugano, Switzerland, now known as Cornèr Arena.
  • C. Guarao
    Guarao is an indigenous language of the Warao people of the Orinoco Delta region in Venezuela.
  • D. Fussa
    Fussa is a city in western Tokyo, Japan, known for hosting Yokota Air Base and various Japan Air Self-Defense Force facilities.
  • E. Bardineto
    Bardineto is a small municipality in the Liguria region of northwestern Italy, known for its mountainous surroundings and proximity to the Ligurian Alps.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4729528b88190bd8a104f6f6d4e69 completed April 19, 2026, 6:13 a.m.
Created at: April 10, 2026, 10:05 a.m.