Triple

T3663750
Position Surface form Disambiguated ID Type / Status
Subject Estremoz E77710 entity
Predicate locatedNear P294 FINISHED
Object Vila Viçosa E195641 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: Vila Viçosa | Statement: [Estremoz, locatedNear, Vila Viçosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila Viçosa
Context triple: [Estremoz, locatedNear, Vila Viçosa]
  • A. Vila Viçosa chosen
    Vila Viçosa is a historic town in Portugal renowned for its marble quarries and as a former residence of the Portuguese royal family.
  • B. Vila do Porto
    Vila do Porto is the main town and oldest settlement in the Azores, located on Santa Maria Island in Portugal.
  • C. Vila Verde
    Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
  • D. Vila de São Sebastião
    Vila de São Sebastião is a civil parish on Terceira Island in the Azores, Portugal, known for its historic architecture and coastal setting within the municipality of Angra do Heroísmo.
  • E. Vila Baleira
    Vila Baleira is the main urban center and administrative hub of Porto Santo Island in Portugal’s Madeira archipelago, known for its proximity to long sandy beaches and historical ties to Christopher Columbus.
  • 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_69ad85dfc4dc8190a441864202ab2a7a completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3fe5eb08190ab15044acf9ac8a9 completed March 8, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48848be788190acde46880918d36b completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.