Triple

T10771684
Position Surface form Disambiguated ID Type / Status
Subject Middle Georgia Regional Airport E254094 entity
Predicate hasICAOIdentifier P36333 FINISHED
Object KMCN E254094 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: KMCN | Statement: [Middle Georgia Regional Airport, hasICAOIdentifier, KMCN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KMCN
Context triple: [Middle Georgia Regional Airport, hasICAOIdentifier, KMCN]
  • A. KMCN chosen
    KMCN is the ICAO airport code for Middle Georgia Regional Airport, a public airport serving the Macon, Georgia area in the United States.
  • B. KMCB
    KMCB is the ICAO airport code for McComb-Pike County Airport, a public airport serving McComb in Pike County, Mississippi.
  • C. KMC
    KMC is the commonly used abbreviation for Kirori Mal College, a prominent constituent college of the University of Delhi in India.
  • D. KMC
    KMC is the municipal governing body responsible for providing and managing civic services and infrastructure in Karachi, Pakistan.
  • E. KMMC
    KMMC is an Indian music conservatory founded by composer A. R. Rahman that offers professional training in Western and Indian classical music and music technology.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d7329a281081909cdc4b971cf69207 completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb0b5c9d8819088edb21a35d8b0dc completed April 14, 2026, 9:25 p.m.
Created at: April 8, 2026, 9:16 p.m.