Triple

T16299403
Position Surface form Disambiguated ID Type / Status
Subject Lamego E395741 entity
Predicate hasNearbyCity P350 FINISHED
Object Viseu E199960 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: Viseu | Statement: [Lamego, hasNearbyCity, Viseu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viseu
Context triple: [Lamego, hasNearbyCity, Viseu]
  • A. Viseu chosen
    Viseu is a historic inland city in central Portugal known for its well-preserved medieval center, wine production, and cultural heritage.
  • B. Sever do Vouga
    Sever do Vouga is a municipality in central Portugal known for its natural landscapes, waterfalls, and rural tourism within the Aveiro District.
  • C. Rio Maior
    Rio Maior is a Portuguese city known for its traditional salt pans and location in the Ribatejo region.
  • D. Golegã
    Golegã is a Portuguese town famed for its equestrian traditions and annual horse fair, located in the Centro Region of Portugal.
  • E. Vira do Minho
    Vira do Minho is a lively traditional Portuguese folk dance from the Minho region, typically performed in circles or pairs to upbeat regional music.
  • 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_6a002da268b881908f17980c48d44419 completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 5:06 a.m.