Triple

T17452920
Position Surface form Disambiguated ID Type / Status
Subject ECoC 2016 E424957 entity
Predicate hasCity P316 FINISHED
Object Donostia NE NERFINISHED

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: Donostia | Statement: [ECoC 2016, hasCity, Donostia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donostia
Context triple: [ECoC 2016, hasCity, Donostia]
  • A. Donostia-San Sebastián chosen
    Donostia-San Sebastián is a coastal city in Spain’s Basque Country renowned for its picturesque bay, beaches, and world-class gastronomy.
  • B. Bilbao
    Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
  • C. Bilbao
    Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
  • D. Pamplona
    Pamplona is a historic Colombian city in the Andean region known for its colonial architecture, religious heritage, and role as an educational and cultural center.
  • E. Pamplona
    Pamplona is a landlocked agricultural municipality in the province of Negros Oriental in the Philippines, known for its hilly terrain and rural communities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4513faa0c8190961cf504c459bf34 completed April 19, 2026, 3:51 a.m.
Created at: April 10, 2026, 5:47 a.m.