Triple

T4473075
Position Surface form Disambiguated ID Type / Status
Subject Konya Airport E98540 entity
Predicate IATAcode P418 FINISHED
Object KYA
KYA is the IATA airport code for Konya Airport, a public and military airport serving the city of Konya in Turkey.
 E441282 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: KYA | Statement: [Konya Airport, IATAcode, KYA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KYA
Context triple: [Konya Airport, IATAcode, KYA]
  • A. YKA
    YKA is the IATA airport code for Kamloops Airport, a regional airport serving the city of Kamloops in British Columbia, Canada.
  • B. KHYA
    KHYA is the ICAO airport code for Barnstable Municipal Airport, a public airport serving Hyannis on Cape Cod, Massachusetts.
  • C. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • D. 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.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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: KYA
Triple: [Konya Airport, IATAcode, KYA]
Generated description
KYA is the IATA airport code for Konya Airport, a public and military airport serving the city of Konya in Turkey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KYA
Target entity description: KYA is the IATA airport code for Konya Airport, a public and military airport serving the city of Konya in Turkey.
  • A. YKA
    YKA is the IATA airport code for Kamloops Airport, a regional airport serving the city of Kamloops in British Columbia, Canada.
  • B. KHYA
    KHYA is the ICAO airport code for Barnstable Municipal Airport, a public airport serving Hyannis on Cape Cod, Massachusetts.
  • C. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • D. 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.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356b95c888190a84bf4a9b2c60aa6 completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b628764bf081909a7a1079d0176c66 completed March 15, 2026, 3:33 a.m.
NEDg Description generation batch_69b6295627848190a7bb6b8943b0e3f1 completed March 15, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_69b629be765c81908c1f6ccfc75604d1 completed March 15, 2026, 3:38 a.m.
Created at: March 12, 2026, 11:35 p.m.