Triple

T12043440
Position Surface form Disambiguated ID Type / Status
Subject European route E70 E286722 entity
Predicate passesThroughCity P416 FINISHED
Object Gijón E269560 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: Gijón | Statement: [European route E70, passesThroughCity, Gijón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gijón
Context triple: [European route E70, passesThroughCity, Gijón]
  • A. Gijón chosen
    Gijón is a coastal city in northern Spain’s Asturias region, known for its major seaport, maritime heritage, and beaches along the Bay of Biscay.
  • B. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • C. Ferrol
    Ferrol is a coastal municipality located on Tablas Island in the province of Romblon in the Philippines.
  • D. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • E. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040d13108190bd1a969fa62aae5a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a62f0fc8190a3d15ccfb23bb788 completed May 2, 2026, 2:29 p.m.
Created at: April 8, 2026, 9:47 p.m.