Triple

T16036971
Position Surface form Disambiguated ID Type / Status
Subject ZAZ E388993 entity
Predicate refersTo P37 FINISHED
Object Zaragoza Airport E271141 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: Zaragoza Airport | Statement: [ZAZ, refersTo, Zaragoza Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaragoza Airport
Context triple: [ZAZ, refersTo, Zaragoza Airport]
  • A. Zaragoza Airport chosen
    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.
  • B. Pamplona Airport
    Pamplona Airport is a regional Spanish airport serving the city of Pamplona and the surrounding Navarre region with domestic and limited international flights.
  • C. Bilbao Airport
    Bilbao Airport is a major international airport in northern Spain serving the city of Bilbao and the Basque Country region.
  • D. 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.
  • E. Badajoz Airport
    Badajoz Airport is a regional Spanish airport serving the autonomous community of Extremadura with domestic commercial flights and military operations.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1833ca66881909475fac23e6fbf86 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff295a0e08190b80d363f0a48094a completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 4:56 a.m.