Triple

T15570396
Position Surface form Disambiguated ID Type / Status
Subject Beiras E374222 entity
Predicate hasWineRegion P285 FINISHED
Object Dão DOC E206259 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: Dão DOC | Statement: [Beiras, hasWineRegion, Dão DOC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dão DOC
Context triple: [Beiras, hasWineRegion, Dão DOC]
  • A. Alentejo DOC
    Alentejo DOC is a prominent Portuguese wine appellation in the Alentejo region, known for its warm climate and production of rich, full-bodied red and white wines.
  • B. Dão wine region chosen
    Dão wine region is a renowned Portuguese appellation in north-central Portugal, known for its high-quality red and white wines, particularly those made from the Touriga Nacional and Encruzado grape varieties.
  • C. Douro Demarcated Region
    The Douro Demarcated Region is a historic wine-producing area in northern Portugal, renowned as one of the world’s oldest demarcated wine regions and the birthplace of Port wine.
  • D. Arruda dos Vinhos
    Arruda dos Vinhos is a Portuguese municipality and wine-producing town located in the Lisbon metropolitan area.
  • E. Figueiró dos Vinhos
    Figueiró dos Vinhos is a municipality in central Portugal known for its forested landscapes, river beaches, and traditional rural character.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e1de0488190b3639fc25f79d343 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c4440a481909699a7eee25a4b24 completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 4:10 a.m.