Triple

T21881663
Position Surface form Disambiguated ID Type / Status
Subject Bemposta E540296 entity
Predicate locatedIn P40 FINISHED
Object Abrantes 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: Abrantes | Statement: [Bemposta, locatedIn, Abrantes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abrantes
Context triple: [Bemposta, locatedIn, Abrantes]
  • A. Abrantes chosen
    Abrantes is a historic Portuguese city in the Santarém District, known for its hilltop castle and strategic location overlooking the Tagus River.
  • B. Seixas
    Seixas is a surname most notably associated with individuals of Portuguese and Sephardic Jewish heritage.
  • C. Aveiro
    Aveiro is a coastal city in central Portugal known for its picturesque canals, colorful moliceiro boats, and distinctive Art Nouveau architecture.
  • D. Serpa
    Serpa is a historic walled town and municipality in Portugal’s Alentejo region, known for its medieval architecture, whitewashed houses, and traditional cheese production.
  • E. Almada
    Almada is a Portuguese city located on the south bank of the Tagus River, opposite Lisbon, known for its panoramic views of the capital and its prominent Cristo Rei statue.
  • 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_69e0c479a98081908ce333853fdd4348 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f118e7a3c48190be1cc285ad4b6496 completed April 28, 2026, 8:30 p.m.
Created at: April 16, 2026, 7:04 p.m.