Triple

T1419286
Position Surface form Disambiguated ID Type / Status
Subject Kenya Airways E31986 entity
Predicate ICAOcode P419 FINISHED
Object KQA
KQA is the ICAO airline designator used to identify Kenya Airways in international aviation operations.
 E162775 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: KQA | Statement: [Kenya Airways, ICAOcode, KQA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KQA
Context triple: [Kenya Airways, ICAOcode, KQA]
  • A. KQ
    KQ is the IATA airline designator for Kenya Airways, the flag carrier of Kenya.
  • B. QA
    QA is the two-letter ISO 3166-1 alpha-2 country code assigned to Qatar for international standardization and identification.
  • C. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • D. Q’s
    Q’s is the nickname commonly used for the former American Basketball Association team the San Diego Conquistadors.
  • E. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • 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: KQA
Triple: [Kenya Airways, ICAOcode, KQA]
Generated description
KQA is the ICAO airline designator used to identify Kenya Airways in international aviation operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KQA
Target entity description: KQA is the ICAO airline designator used to identify Kenya Airways in international aviation operations.
  • A. KQ chosen
    KQ is the IATA airline designator for Kenya Airways, the flag carrier of Kenya.
  • B. QA
    QA is the two-letter ISO 3166-1 alpha-2 country code assigned to Qatar for international standardization and identification.
  • C. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • D. Q’s
    Q’s is the nickname commonly used for the former American Basketball Association team the San Diego Conquistadors.
  • E. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c40631e881909ddf81a2eb84af1c completed March 1, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad015f5ad08190aaa0d1063432af2b completed March 8, 2026, 4:55 a.m.
NEDg Description generation batch_69ad01f8028881909af95e9f61a17e88 completed March 8, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_69ad02c618c48190abf3e16d9f85e703 completed March 8, 2026, 5:01 a.m.
Created at: March 1, 2026, 7:59 p.m.