Triple

T17156776
Position Surface form Disambiguated ID Type / Status
Subject Aviación Nacional E416361 entity
Predicate headquartersLocation P62 FINISHED
Object Burgos E173961 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: Burgos | Statement: [Aviación Nacional, headquartersLocation, Burgos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burgos
Context triple: [Aviación Nacional, headquartersLocation, Burgos]
  • A. Burgos chosen
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • B. Burgos
    Burgos is a small coastal municipality on the northern tip of Siargao Island in the Philippines, known for its quiet beaches and surf spots.
  • C. Badajoz
    Badajoz is a historic city in western Spain near the Portuguese border, known for its medieval fortress and role as a strategic frontier stronghold.
  • D. Valladolid
    Valladolid is a historic colonial city in Mexico’s Yucatán Peninsula, known for its Spanish architecture, cenotes, and proximity to Mayan archaeological sites.
  • E. Valladolid
    Valladolid is a small municipality located in the Lempira Department of western Honduras, known for its rural character and mountainous terrain.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f40bf9ec8190b16372bcd091db9b completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a018c38b1ec819092a551e2683a4b93 completed May 11, 2026, 7:58 a.m.
Created at: April 10, 2026, 5:37 a.m.