Triple

T14478531
Position Surface form Disambiguated ID Type / Status
Subject Port of Gandia E359039 entity
Predicate regionServed P82 FINISHED
Object Gandia E231608 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: Gandia | Statement: [Port of Gandia, regionServed, Gandia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gandia
Context triple: [Port of Gandia, regionServed, Gandia]
  • A. Gandia chosen
    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.
  • B. Alcoy
    Alcoy is an industrial and historically significant city in southeastern Spain, known for its textile heritage, modernist architecture, and famous Moors and Christians festival.
  • C. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • D. 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.
  • E. 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.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9248edb48190a74eb032aeaac027 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94a7187c81909f173c2fb70509f5 completed May 8, 2026, 7:45 a.m.
Created at: April 10, 2026, 1:20 a.m.