Triple

T15028995
Position Surface form Disambiguated ID Type / Status
Subject Castelo Branco District E378290 entity
Predicate hasTown P847 FINISHED
Object Belmonte E374153 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: Belmonte | Statement: [Castelo Branco District, hasTown, Belmonte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belmonte
Context triple: [Castelo Branco District, hasTown, Belmonte]
  • A. Belmonte chosen
    Belmonte is a historic town in Portugal known for its medieval castle and strong Jewish heritage, located in the country's Centro Region.
  • B. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • C. Moncalvo
    Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
  • D. Bombarral
    Bombarral is a small Portuguese town in the Oeste subregion known for its wine production and agricultural landscape.
  • E. Balcarce
    Balcarce is a city in Buenos Aires Province, Argentina, known for its agricultural economy, motorsport heritage, and as the birthplace of racing legend Juan Manuel Fangio.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7e0e8c88190ac6f5786b4d4040f completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5b4d58481908afbc89263e07b50 completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 2:58 a.m.