Triple

T8457689
Position Surface form Disambiguated ID Type / Status
Subject Viseu E199960 entity
Predicate knownFor P22 FINISHED
Object Dão wine region 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 wine region | Statement: [Viseu, knownFor, Dão wine region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dão wine region
Context triple: [Viseu, knownFor, Dão wine region]
  • A. 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.
  • B. 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.
  • C. Vinho Verde region
    The Vinho Verde region is a renowned wine-producing area in northwestern Portugal, famous for its young, light, and often slightly sparkling white wines.
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe49064f881909391d565b97e9886 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1dea01c481909496ebfca4e9916e completed April 2, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:10 p.m.