Triple

T20074086
Position Surface form Disambiguated ID Type / Status
Subject Terminal C (former) E499812 entity
Predicate hasIATAAirport P17503 FINISHED
Object MCI 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: MCI | Statement: [Terminal C (former), hasIATAAirport, MCI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MCI
Context triple: [Terminal C (former), hasIATAAirport, MCI]
  • A. MCI chosen
    MCI is a major commercial airport serving the Kansas City metropolitan area in Missouri, United States.
  • B. MCI
    MCI was the former statutory body responsible for establishing and maintaining high standards of medical education and registration of medical practitioners in India.
  • C. MCI-Shirley
    MCI-Shirley is a medium- and minimum-security state prison for men located in Shirley, Massachusetts.
  • D. MCI Inc.
    MCI Inc. was a major American telecommunications company and long-distance service provider that played a key role in breaking AT&T’s monopoly before eventually being acquired by Verizon.
  • E. MCA
    MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66439efe881909a068c3f05022421 completed April 20, 2026, 5:36 p.m.
Created at: April 11, 2026, 3:40 p.m.