Triple

T22049253
Position Surface form Disambiguated ID Type / Status
Subject Kruger Mpumalanga International Airport E544839 entity
Predicate ICAOcode P419 FINISHED
Object FAKN
FAKN is the ICAO airport code assigned to Kruger Mpumalanga International Airport in South Africa.
 E1515653 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: FAKN | Statement: [Kruger Mpumalanga International Airport, ICAOcode, FAKN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FAKN
Context triple: [Kruger Mpumalanga International Airport, ICAOcode, FAKN]
  • A. FAK
    FAK is the official abbreviation for the Royal Danish Defence College, Denmark’s primary institution for military education and research.
  • B. FAKM
    FAKM is the ICAO airport code assigned to Kimberley Airport in South Africa.
  • C. FukuDai
    FukuDai is the commonly used abbreviated name for Fukuoka University, a major private university located in Fukuoka, Japan.
  • D. FAJ
    FAJ is the commonly used abbreviation for the Cariduros de Fajardo, a professional basketball team based in Fajardo, Puerto Rico.
  • E. FANK
    FANK was the acronym for the Khmer National Armed Forces, the military of the pro-U.S. Lon Nol government in Cambodia during the Cambodian Civil War.
  • 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: FAKN
Triple: [Kruger Mpumalanga International Airport, ICAOcode, FAKN]
Generated description
FAKN is the ICAO airport code assigned to Kruger Mpumalanga International Airport in South Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FAKN
Target entity description: FAKN is the ICAO airport code assigned to Kruger Mpumalanga International Airport in South Africa.
  • A. FAK
    FAK is the official abbreviation for the Royal Danish Defence College, Denmark’s primary institution for military education and research.
  • B. FAKM
    FAKM is the ICAO airport code assigned to Kimberley Airport in South Africa.
  • C. FukuDai
    FukuDai is the commonly used abbreviated name for Fukuoka University, a major private university located in Fukuoka, Japan.
  • D. FAJ
    FAJ is the commonly used abbreviation for the Cariduros de Fajardo, a professional basketball team based in Fajardo, Puerto Rico.
  • E. FANK
    FANK was the acronym for the Khmer National Armed Forces, the military of the pro-U.S. Lon Nol government in Cambodia during the Cambodian Civil War.
  • 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_69e11e32445c8190ab97089b48a130bb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1283191e48190b4ddc84138243327 completed April 28, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a7b79594c8190b66439167d7a3cbd completed May 18, 2026, 2:37 a.m.
NEDg Description generation batch_6a0a7cb2b0c88190930290efe1d8371a completed May 18, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_6a0a7e131ae48190a564a86d3d691e1a completed May 18, 2026, 2:48 a.m.
Created at: April 16, 2026, 8:26 p.m.