Triple

T6974758
Position Surface form Disambiguated ID Type / Status
Subject Kenneth Kaunda International Airport E161689 entity
Predicate IATAcode P418 FINISHED
Object LUN
LUN is the IATA airport code for Kenneth Kaunda International Airport, the main international gateway serving Lusaka, the capital city of Zambia.
E633667 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: LUN | Statement: [Kenneth Kaunda International Airport, IATAcode, LUN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LUN
Context triple: [Kenneth Kaunda International Airport, IATAcode, LUN]
  • A. Lunan
    Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
  • B. Lunice
    Lunice is a Canadian electronic music producer and DJ known for his innovative trap-influenced beats and as one half of the duo TNGHT.
  • C. Luneta
    Luneta is the historic urban park in Manila, Philippines, renowned as a national landmark and popular public gathering place.
  • D. LBN
    LBN is the three-letter ISO 3166-1 alpha-3 country code for Lebanon.
  • E. Lont
    Lont is the ISO 15924 four-letter code assigned to the Lontara script used for writing several languages of Sulawesi, Indonesia.
  • 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: LUN
Triple: [Kenneth Kaunda International Airport, IATAcode, LUN]
Generated description
LUN is the IATA airport code for Kenneth Kaunda International Airport, the main international gateway serving Lusaka, the capital city of Zambia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LUN
Target entity description: LUN is the IATA airport code for Kenneth Kaunda International Airport, the main international gateway serving Lusaka, the capital city of Zambia.
  • A. Lunan
    Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
  • B. Lunice
    Lunice is a Canadian electronic music producer and DJ known for his innovative trap-influenced beats and as one half of the duo TNGHT.
  • C. Luneta
    Luneta is the historic urban park in Manila, Philippines, renowned as a national landmark and popular public gathering place.
  • D. LBN
    LBN is the three-letter ISO 3166-1 alpha-3 country code for Lebanon.
  • E. Lont
    Lont is the ISO 15924 four-letter code assigned to the Lontara script used for writing several languages of Sulawesi, Indonesia.
  • 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_69c68854a0d88190bc0bf82263f1afce completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db3bda908190a10a91dc8d043ef1 completed March 27, 2026, 7:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761a6bbdc81908c96871f151db279 completed March 28, 2026, 5:05 a.m.
NEDg Description generation batch_69c7639074f48190bc095f18fc35c08b completed March 28, 2026, 5:13 a.m.
NED2 Entity disambiguation (via description) batch_69c76435fd2c819099143ea12f21d095 completed March 28, 2026, 5:16 a.m.
Created at: March 27, 2026, 2:30 p.m.