Triple

T22585586
Position Surface form Disambiguated ID Type / Status
Subject Douglas Municipal Airport E564781 entity
Predicate hasFAACode P34770 FINISHED
Object CLT
CLT is the FAA location identifier for Charlotte Douglas International Airport, a major commercial airport serving Charlotte, North Carolina.
 E120855 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: CLT | Statement: [Douglas Municipal Airport, hasFAACode, CLT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CLT
Context triple: [Douglas Municipal Airport, hasFAACode, CLT]
  • A. 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.
  • B. CLT
    CLT is the IATA airport code for Charlotte Douglas International Airport, a major airline hub in Charlotte, North Carolina.
  • C. CLT
    CLT is the National Rail station code for Clacton-on-Sea railway station in Essex, England.
  • D. CLT
    CLT is the standard time zone used in Chile, typically corresponding to UTC−4 hours.
  • E. CLT
    CLT is the station code for Kozhikode railway station, a major rail hub in the Indian state of Kerala.
  • 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: CLT
Triple: [Douglas Municipal Airport, hasFAACode, CLT]
Generated description
CLT is the FAA location identifier for Charlotte Douglas International Airport, a major commercial airport serving Charlotte, North Carolina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CLT
Target entity description: CLT is the FAA location identifier for Charlotte Douglas International Airport, a major commercial airport serving Charlotte, North Carolina.
  • A. 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.
  • B. CLT chosen
    CLT is the IATA airport code for Charlotte Douglas International Airport, a major airline hub in Charlotte, North Carolina.
  • C. CLT
    CLT is the National Rail station code for Clacton-on-Sea railway station in Essex, England.
  • D. CLT
    CLT is the standard time zone used in Chile, typically corresponding to UTC−4 hours.
  • E. CLT
    CLT is the station code for Kozhikode railway station, a major rail hub in the Indian state of Kerala.
  • F. None of above.

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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615c18f88190ad4f23639d15f337 completed April 29, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b4df155e881909d68b23e61d2bfb2 completed May 18, 2026, 5:35 p.m.
NEDg Description generation batch_6a0b51f28ffc81909792131738d8ea93 completed May 18, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_6a0b525e0cf08190a8b18165034d3d30 completed May 18, 2026, 5:54 p.m.
Created at: April 17, 2026, 2:45 p.m.