Triple

T17124862
Position Surface form Disambiguated ID Type / Status
Subject Beira Interior E415565 entity
Predicate containsTown 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: [Beira Interior, containsTown, Belmonte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belmonte
Context triple: [Beira Interior, containsTown, 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. Belmonte de San José
    Belmonte de San José is a small municipality in the province of Teruel, Aragon, Spain, known for its traditional Aragonese architecture and rural setting within the Matarranya comarca.
  • C. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • D. 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.
  • E. Bombarral
    Bombarral is a small Portuguese town in the Oeste subregion known for its wine production and agricultural landscape.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f025fce481908e261f2e363e14f9 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a12a7288190911c1be2667916c0 completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:36 a.m.