Triple

T22009811
Position Surface form Disambiguated ID Type / Status
Subject Igualada E543545 entity
Predicate locatedIn P40 FINISHED
Object Anoia 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: Anoia | Statement: [Igualada, locatedIn, Anoia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anoia
Context triple: [Igualada, locatedIn, Anoia]
  • A. Anoia chosen
    Anoia is a comarca (county) in central Catalonia, Spain, known for its mix of industrial towns and rural landscapes, with Igualada as its capital.
  • B. Porrera
    Porrera is a village and municipality in Catalonia, Spain, known for its wine production within the renowned Priorat wine region.
  • C. Gironella
    Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
  • D. Valdemaqueda
    Valdemaqueda is a small municipality in the Community of Madrid, Spain, known for its rural landscape and proximity to the Sierra de Guadarrama.
  • E. Urqueira
    Urqueira is a small locality or parish within the municipality of Ourém in central Portugal.
  • 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_69e11e2db934819095556760c7d85e4d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127a376048190a78ba7efd303b58a completed April 28, 2026, 9:33 p.m.
Created at: April 16, 2026, 8:22 p.m.