Triple

T16858819
Position Surface form Disambiguated ID Type / Status
Subject Santiago–Rosalía de Castro Airport E409855 entity
Predicate cityServed P82 FINISHED
Object Pontevedra E221545 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: Pontevedra | Statement: [Santiago–Rosalía de Castro Airport, cityServed, Pontevedra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pontevedra
Context triple: [Santiago–Rosalía de Castro Airport, cityServed, Pontevedra]
  • A. Pontevedra chosen
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • B. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • C. A Coruña
    A Coruña is a coastal city in northwestern Spain known for its historic lighthouse, the Tower of Hercules, and its role as an important cultural and economic center in the region.
  • D. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • E. Ferrol
    Ferrol is a coastal municipality located on Tablas Island in the province of Romblon in the Philippines.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b501f72881909f7600311705fb33 completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2a6f2c48190874839f78f943fdb completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:24 a.m.