Triple

T13536324
Position Surface form Disambiguated ID Type / Status
Subject Calafia Airlines E323269 entity
Predicate servesDestination P2066 FINISHED
Object Puerto Peñasco E136106 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: Puerto Peñasco | Statement: [Calafia Airlines, servesDestination, Puerto Peñasco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Peñasco
Context triple: [Calafia Airlines, servesDestination, Puerto Peñasco]
  • A. Puerto Peñasco chosen
    Puerto Peñasco is a Mexican resort city on the Gulf of California, popular for its beaches and tourism, especially among visitors from the nearby U.S. Southwest.
  • B. Nogales
    Nogales is a municipality and town in the state of Veracruz, Mexico, known for its mountainous terrain and role as part of the Orizaba metropolitan area.
  • C. Nogales
    Nogales is a Chilean municipality located in the Province of Quillota in the Valparaíso Region.
  • D. Nogales
    Nogales is a small municipality in the Tierra de Barros comarca of the province of Badajoz, in the autonomous community of Extremadura, Spain.
  • E. Acaponeta
    Acaponeta is a town and municipality in the Mexican state of Nayarit, known for its agricultural economy and location near the Acaponeta River.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbe39948190808062d4eff91841 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d9a448c81908fa57a909a9097f7 completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:44 p.m.