Triple

T14380647
Position Surface form Disambiguated ID Type / Status
Subject Alcoy campus E356591 entity
Predicate regionServed P82 FINISHED
Object Alcoy E947073 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: Alcoy | Statement: [Alcoy campus, regionServed, Alcoy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alcoy
Context triple: [Alcoy campus, regionServed, Alcoy]
  • A. Alcoy chosen
    Alcoy is an industrial and historically significant city in southeastern Spain, known for its textile heritage, modernist architecture, and famous Moors and Christians festival.
  • B. Alicante
    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.
  • C. Burjassot
    Burjassot is a municipality in the metropolitan area of Valencia, Spain, known for its residential character and proximity to major university and research facilities.
  • D. Denia
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • E. Gandia
    Gandia is a coastal city in eastern Spain known for its Mediterranean beaches, historical heritage, and role as a tourist destination in the province of Valencia.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900bbfb08190a1e56f281a2374c0 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648135188190af86b1b2be2fe0e0 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:16 a.m.