Triple

T8689899
Position Surface form Disambiguated ID Type / Status
Subject Dão wine region E206259 entity
Predicate locatedIn P40 FINISHED
Object Beira Alta E385153 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: Beira Alta | Statement: [Dão wine region, locatedIn, Beira Alta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beira Alta
Context triple: [Dão wine region, locatedIn, Beira Alta]
  • A. Beira Alta chosen
    Beira Alta is a historical province in north-central Portugal known for its mountainous landscapes, fortified towns, and wine-producing regions.
  • B. Cantanhede
    Cantanhede is a Portuguese municipality in the Centro Region known for its wine production, agricultural activity, and proximity to the Atlantic coast.
  • C. Braz de Aviz
    Braz de Aviz is a Brazilian cardinal of the Roman Catholic Church known for his leadership roles in the Vatican, including as prefect of the Dicastery for Institutes of Consecrated Life and Societies of Apostolic Life.
  • D. Gouveia
    Gouveia is a municipality and town in central Portugal, situated in the Serra da Estrela mountain range and known for its natural landscapes and wool industry heritage.
  • E. Cacilhas
    Cacilhas is a riverside district in Almada, Portugal, known for its ferry link to Lisbon and its waterfront restaurants and bars.
  • 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5734602c81909a0687e00f4a4a26 completed March 31, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3df73b88190b67138ee5129de8b completed April 2, 2026, 10:55 p.m.
Created at: March 30, 2026, 6:33 p.m.