Triple

T22119837
Position Surface form Disambiguated ID Type / Status
Subject Sobral de Monte Agraço E546635 entity
Predicate borderedBy P224 FINISHED
Object Alenquer 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: Alenquer | Statement: [Sobral de Monte Agraço, borderedBy, Alenquer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alenquer
Context triple: [Sobral de Monte Agraço, borderedBy, Alenquer]
  • A. Alenquer chosen
    Alenquer is a historic Portuguese town and municipality in the Lisbon District, known for its wine production and scenic location along the banks of the River Alcabrichel.
  • B. Alenquer
    Alenquer is a municipality in the Brazilian state of Pará, located in the Lower Amazon region and known for its Amazonian riverside landscapes and biodiversity.
  • C. Sabugal
    Sabugal is a historic municipality and town in central Portugal, known for its medieval castle and scenic location near the Spanish border.
  • D. Leiria
    Leiria is a historic city in central Portugal known for its medieval hilltop castle and role as a regional administrative and cultural center.
  • E. Bragança
    Bragança is a historic city in northeastern Portugal known for its well-preserved medieval castle and role as the former seat of the House of Braganza.
  • 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_69e11e38b3848190ac3a4fa97d56e65a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12950f5348190b204fbc347fd5dab completed April 28, 2026, 9:40 p.m.
Created at: April 16, 2026, 8:31 p.m.