Triple

T4593443
Position Surface form Disambiguated ID Type / Status
Subject European Union administrative centres E103550 entity
Predicate hasMember P10 FINISHED
Object Alicante E326236 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: Alicante | Statement: [European Union administrative centres, hasMember, Alicante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alicante
Context triple: [European Union administrative centres, hasMember, Alicante]
  • A. Alicante chosen
    Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial center.
  • B. Valencia
    Valencia is a major Spanish coastal city known for its historic architecture, vibrant culture, and significant role as a key Mediterranean trade and tourism hub.
  • C. Valencia
    Valencia is a municipality in the Philippine province of Negros Oriental known for its cool climate, geothermal energy resources, and natural attractions such as waterfalls and mountain landscapes.
  • D. Valencia
    Valencia is a city in Ecuador that serves as the capital of Los Ríos Province’s Valencia Canton and is known for its agricultural surroundings and tropical climate.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd593cf8508190acfc6ddb5716e80a completed March 20, 2026, 2:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed8fed2208190a3e340190356e67f completed March 21, 2026, 5:44 p.m.
Created at: March 20, 2026, 1:11 p.m.