Triple

T7959124
Position Surface form Disambiguated ID Type / Status
Subject Badajoz E184815 entity
Predicate hasAirport P105 FINISHED
Object Badajoz Airport E225020 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: Badajoz Airport | Statement: [Badajoz, hasAirport, Badajoz Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Badajoz Airport
Context triple: [Badajoz, hasAirport, Badajoz Airport]
  • A. Badajoz Airport chosen
    Badajoz Airport is a regional Spanish airport serving the autonomous community of Extremadura with domestic commercial flights and military operations.
  • B. Burgos Airport
    Burgos Airport is a regional public airport in Burgos, Spain, providing domestic air services and connecting the city to the national air transport network.
  • C. Valladolid Airport
    Valladolid Airport is a regional Spanish airport serving the city of Valladolid and the surrounding Castile and León region, handling domestic and limited international flights.
  • D. Albacete Airport
    Albacete Airport is a regional Spanish airport near the city of Albacete that serves both civil and military aviation operations.
  • E. Murcia–San Javier Airport
    Murcia–San Javier Airport is a Spanish airport in the Region of Murcia that serves both civilian flights and military aviation activities.
  • 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_69ca8293a2388190aace944d7ed9c0c0 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b80050c81909b2db95ade495052 completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe07d31a881909e891fdd73c4467b completed March 31, 2026, 2:55 p.m.
Created at: March 30, 2026, 5:11 p.m.