Triple

T10824922
Position Surface form Disambiguated ID Type / Status
Subject Vitoria-Gasteiz E255472 entity
Predicate shortName P43 FINISHED
Object Vitoria E255472 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: Vitoria | Statement: [Vitoria-Gasteiz, shortName, Vitoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vitoria
Context triple: [Vitoria-Gasteiz, shortName, Vitoria]
  • A. Vitoria chosen
    Vitoria is a historic city in northern Spain, known today as Vitoria-Gasteiz, the capital of the Basque Country and the site of the pivotal 1813 Battle of Vitoria during the Peninsular War.
  • B. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • C. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • D. Valencia
    Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • E. Valencia
    Valencia was the original working title for the 2016 psychological thriller film "10 Cloverfield Lane."
  • 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d734d0389c819090a892693c4046ed completed April 9, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2166293808190b7ed1620dfc8a158 completed April 17, 2026, 11:15 a.m.
Created at: April 8, 2026, 9:19 p.m.