Triple

T10946101
Position Surface form Disambiguated ID Type / Status
Subject Cesena E258600 entity
Predicate twinTown P1072 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: [Cesena, twinTown, Vila Viçosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila Viçosa
Context triple: [Cesena, twinTown, 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 do Porto
    Vila do Porto is the main town and oldest settlement in the Azores, located on Santa Maria Island in Portugal.
  • D. Vila Verde
    Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
  • E. 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.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770e9a89081908979efd1d9e6af66 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c3c885081908edcece772b2e759 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.