Triple

T5915518
Position Surface form Disambiguated ID Type / Status
Subject Huesca province E131569 entity
Predicate contains P35 FINISHED
Object Barbastro E332927 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: Barbastro | Statement: [Huesca province, contains, Barbastro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbastro
Context triple: [Huesca province, contains, Barbastro]
  • A. Barbastro chosen
    Barbastro is a historic town in the Aragon region of northeastern Spain, known for its wine production and medieval architecture.
  • B. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • C. Montilla
    Montilla is a town in the province of Córdoba, Andalusia, Spain, known for its wine production and historical significance.
  • D. Sagunto
    Sagunto is a historic coastal town in eastern Spain renowned for its ancient Roman theatre and hilltop castle overlooking the Mediterranean.
  • E. Tarragona
    Tarragona is a historic port city in northeastern Spain, renowned for its well-preserved Roman ruins and status as a major cultural and economic center in Catalonia.
  • 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_69c008593a44819081a07ae0efe6c574 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c037bb538c8190acc514c2d49359f4 completed March 22, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c02430bc8190a63b91b6dbdbc9f2 completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 3:59 p.m.