Triple

T6281295
Position Surface form Disambiguated ID Type / Status
Subject Aena E140786 entity
Predicate operates P24 FINISHED
Object Valladolid Airport E75361 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: Valladolid Airport | Statement: [Aena, operates, Valladolid Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valladolid Airport
Context triple: [Aena, operates, Valladolid Airport]
  • A. Valladolid Airport chosen
    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.
  • B. Badajoz Airport
    Badajoz Airport is a regional Spanish airport serving the autonomous community of Extremadura with domestic commercial flights and military operations.
  • C. Asturias Airport
    Asturias Airport is a regional international airport in northern Spain serving the Asturias region with domestic and limited international flights.
  • D. 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.
  • E. Zaragoza Airport
    Zaragoza Airport is an international airport in northeastern Spain that serves the city of Zaragoza and functions as both a civilian and important military and cargo hub.
  • 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_69c008cd17c8819082b82d3fbeb68047 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063dee62881908347283f16dcbe68 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7005e8c2c81909729f7ab3ae0287d completed March 27, 2026, 10:10 p.m.
Created at: March 22, 2026, 4:26 p.m.