Triple

T14975386
Position Surface form Disambiguated ID Type / Status
Subject John IV of Portugal E373432 entity
Predicate birthPlace P1 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: [John IV of Portugal, birthPlace, Vila Viçosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila Viçosa
Context triple: [John IV of Portugal, birthPlace, 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 Flor
    Vila Flor is a municipality in northern Portugal, situated in the Douro region known for its wine production and scenic landscapes.
  • C. Vila Prudente
    Vila Prudente is a metro station in São Paulo, Brazil, serving as a key terminal and transfer point on the city’s rapid transit network.
  • D. Vila do Porto
    Vila do Porto is the main town and oldest settlement in the Azores, located on Santa Maria Island in Portugal.
  • E. Vila Verde
    Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6e8733081908e06b53746eb6eb6 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe8beac05c8190bf19ec8bd1eab2d8 completed May 9, 2026, 1:20 a.m.
Created at: April 10, 2026, 2:51 a.m.