Triple

T16299404
Position Surface form Disambiguated ID Type / Status
Subject Lamego E395741 entity
Predicate hasNearbyCity P350 FINISHED
Object Peso da Régua E996725 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: Peso da Régua | Statement: [Lamego, hasNearbyCity, Peso da Régua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peso da Régua
Context triple: [Lamego, hasNearbyCity, Peso da Régua]
  • A. Peso da Régua
    Peso da Régua is a Portuguese city in the Douro Valley known as a key hub for the region’s famous port wine production and river tourism.
  • B. Régua chosen
    Régua, officially Peso da Régua, is a town in northern Portugal known as a key hub of the Douro wine region and a traditional center for Port wine transport.
  • C. Tanguá
    Tanguá is a small municipality in the state of Rio de Janeiro, Brazil, known for its rural character and integration into the greater Rio de Janeiro metropolitan area.
  • D. Putijarra
    Putijarra is an Australian Aboriginal language traditionally spoken by the Martu people of the Western Desert region.
  • E. Capileira
    Capileira is a picturesque mountain village in Spain’s Alpujarras region, known for its traditional whitewashed houses and dramatic location on the southern slopes of the Sierra Nevada.
  • 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_69d87f23bb088190a16fbb91a1957ea5 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e30ee288190b78807b60cb18e22 completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f9d7ef48190b7acebebcb9608c3 completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:06 a.m.