Triple

T8534960
Position Surface form Disambiguated ID Type / Status
Subject Vinho Verde region E202054 entity
Predicate subregion P747 FINISHED
Object Monção e Melgaço E716723 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: Monção e Melgaço | Statement: [Vinho Verde region, subregion, Monção e Melgaço]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monção e Melgaço
Context triple: [Vinho Verde region, subregion, Monção e Melgaço]
  • A. Monção chosen
    Monção is a historic town and municipality in northern Portugal, known for its fortified medieval center and production of Vinho Verde wines along the Minho River.
  • B. Lamego
    Lamego is a historic city in northern Portugal known for its baroque Sanctuary of Our Lady of Remedies and its location in the Douro wine region.
  • C. Carrazeda de Ansiães
    Carrazeda de Ansiães is a municipality in northeastern Portugal known for its wine production, historical heritage, and location within the Douro wine region.
  • D. Montemor-o-Velho
    Montemor-o-Velho is a historic Portuguese town and municipality in central Portugal, known for its medieval castle overlooking the Mondego River and surrounding agricultural plains.
  • E. Covilhã
    Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6a295c88190a432a060ee73f04e completed March 31, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d8332cc819083c86e0dc58bcc37 completed April 2, 2026, 1:22 p.m.
Created at: March 30, 2026, 6:17 p.m.