Triple

T13452971
Position Surface form Disambiguated ID Type / Status
Subject Sporting de Gijón E311156 entity
Predicate location P40 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: [Sporting de Gijón, location, Gijón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gijón
Context triple: [Sporting de Gijón, location, 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaefae85481909e6a59797cbb25e7 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7399c539c819080802b620da6fcfc completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:41 p.m.