Triple

T1127601
Position Surface form Disambiguated ID Type / Status
Subject Charlotte Douglas International Airport E24755 entity
Predicate ICAOcode P419 FINISHED
Object KCLT
KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
E127543 NE FINISHED

How this triple was built (4 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: KCLT | Statement: [Charlotte Douglas International Airport, ICAOcode, KCLT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KCLT
Context triple: [Charlotte Douglas International Airport, ICAOcode, KCLT]
  • A. KSLC
    KSLC is the ICAO airport code for Salt Lake City International Airport, a major air transportation hub serving Salt Lake City, Utah.
  • B. KWT
    KWT is the three-letter ISO 3166-1 alpha-3 country code assigned to Kuwait.
  • C. KLSV
    KLSV is the ICAO airport code for Nellis Air Force Base, a major United States Air Force installation near Las Vegas, Nevada.
  • D. KLu
    KLu is the commonly used abbreviation for the Royal Netherlands Air Force, the aerial warfare branch of the Dutch armed forces.
  • E. CLT
    CLT is a fundamental statistical principle stating that the sum or average of many independent, identically distributed random variables tends to follow a normal distribution, regardless of the original distribution.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KCLT
Triple: [Charlotte Douglas International Airport, ICAOcode, KCLT]
Generated description
KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KCLT
Target entity description: KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
  • A. KSLC
    KSLC is the ICAO airport code for Salt Lake City International Airport, a major air transportation hub serving Salt Lake City, Utah.
  • B. KWT
    KWT is the three-letter ISO 3166-1 alpha-3 country code assigned to Kuwait.
  • C. KLSV
    KLSV is the ICAO airport code for Nellis Air Force Base, a major United States Air Force installation near Las Vegas, Nevada.
  • D. KLu
    KLu is the commonly used abbreviation for the Royal Netherlands Air Force, the aerial warfare branch of the Dutch armed forces.
  • E. CLT
    CLT is a fundamental statistical principle stating that the sum or average of many independent, identically distributed random variables tends to follow a normal distribution, regardless of the original distribution.
  • F. None of above. chosen

Provenance (5 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdd39b88190bf46de38818fe2df completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac53a16a5881908e6c6f7fafe87107 completed March 7, 2026, 4:34 p.m.
NEDg Description generation batch_69ac53f04ad081908f1536f17e65f633 completed March 7, 2026, 4:36 p.m.
NED2 Entity disambiguation (via description) batch_69ac54971fc88190b009a05180f10cf5 completed March 7, 2026, 4:38 p.m.
Created at: March 1, 2026, 7:44 p.m.