Triple

T14270639
Position Surface form Disambiguated ID Type / Status
Subject Gaspar Melchor de Jovellanos E353773 entity
Predicate birthPlace P1 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: [Gaspar Melchor de Jovellanos, birthPlace, Gijón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gijón
Context triple: [Gaspar Melchor de Jovellanos, birthPlace, 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 province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • E. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • 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_69d8278d25148190abf1a8c8f5f533ad completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de657fe6708190b41de48c43cff647 completed April 14, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c31654c81908f53d4c21e255afb completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:10 a.m.