Triple

T20568181
Position Surface form Disambiguated ID Type / Status
Subject Terminal 2 (Cancún International Airport) E505017 entity
Predicate IATAAirportCodeOfParent P2569 FINISHED
Object CUN NE NERFINISHED

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: CUN | Statement: [Terminal 2 (Cancún International Airport), IATAAirportCodeOfParent, CUN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CUN
Context triple: [Terminal 2 (Cancún International Airport), IATAAirportCodeOfParent, CUN]
  • A. CUN chosen
    CUN is the IATA airport code for Cancún International Airport, a major gateway for international tourism to Mexico’s Caribbean coast.
  • B. CNU
    CNU is a professional organization that promotes walkable, mixed-use neighborhood development and sustainable urban design principles.
  • C. CNU
    CNU is a major national research university located in Daejeon, South Korea, known for its comprehensive academic programs and strong emphasis on science and technology.
  • D. CNU
    CNU is the commonly used abbreviation for Chonnam National University, a major national research university in Gwangju, South Korea.
  • E. CNU
    CNU is a public liberal arts university located in Newport News, Virginia, known for its strong undergraduate programs and emphasis on leadership and civic engagement.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a7a3fdc08190a34dcf4c4e51f078 completed April 20, 2026, 10:24 p.m.
Created at: April 16, 2026, 11:39 a.m.