Triple

T8540961
Position Surface form Disambiguated ID Type / Status
Subject Kenya Airports Authority E202191 entity
Predicate abbreviation P43 FINISHED
Object KAA
KAA is the state corporation responsible for managing and operating Kenya’s civil airports and airstrips.
 E741131 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: KAA | Statement: [Kenya Airports Authority, abbreviation, KAA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KAA
Context triple: [Kenya Airports Authority, abbreviation, KAA]
  • A. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • B. KAU
    KAU is the IATA airport code for Kauhava Air Base, a former military airfield in Kauhava, Finland.
  • C. KCA
    KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • D. KAIA
    KAIA is a major international airport in Jeddah, Saudi Arabia, serving as a key gateway for pilgrims traveling to the holy cities of Mecca and Medina.
  • E. 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.
  • 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: KAA
Triple: [Kenya Airports Authority, abbreviation, KAA]
Generated description
KAA is the state corporation responsible for managing and operating Kenya’s civil airports and airstrips.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KAA
Target entity description: KAA is the state corporation responsible for managing and operating Kenya’s civil airports and airstrips.
  • A. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • B. KAU
    KAU is the IATA airport code for Kauhava Air Base, a former military airfield in Kauhava, Finland.
  • C. KCA
    KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • D. KAIA
    KAIA is a major international airport in Jeddah, Saudi Arabia, serving as a key gateway for pilgrims traveling to the holy cities of Mecca and Medina.
  • E. 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.
  • 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_69ca832461e88190a654c5e44e233aa8 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6e10bc081909a7210c577b807fb completed March 31, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6da3d65c819087ed6b46dfc35885 completed April 2, 2026, 1:22 p.m.
NEDg Description generation batch_69ce6ec3b080819082d64646d453541d completed April 2, 2026, 1:27 p.m.
NED2 Entity disambiguation (via description) batch_69ce6fe928d48190824e7a94fea5cfc0 completed April 2, 2026, 1:32 p.m.
Created at: March 30, 2026, 6:18 p.m.