Triple

T11827447
Position Surface form Disambiguated ID Type / Status
Subject Espinar Province E281292 entity
Predicate namedAfter P63 FINISHED
Object Espinar E949726 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: Espinar | Statement: [Espinar Province, namedAfter, Espinar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Espinar
Context triple: [Espinar Province, namedAfter, Espinar]
  • A. Espinar chosen
    Espinar is a town in southern Peru that serves as an administrative and commercial center in the Andean highlands.
  • B. Escalona
    Escalona is a historic Spanish town whose name is associated with the noble title of Duke of Escalona.
  • C. Cangas de Onís
    Cangas de Onís is a historic town in northern Spain’s Asturias region, known as the first capital of the Kingdom of Asturias and a gateway to the Picos de Europa.
  • D. Osuna
    Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
  • E. Espín
    Espín is a Spanish surname notably borne by Cuban revolutionary and feminist leader Vilma Espín.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5ec3a148190bb184ba0d481b16a completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f2812007dc81908e56fd47b2a94836 completed April 29, 2026, 10:07 p.m.
Created at: April 8, 2026, 9:43 p.m.