Triple

T1398170
Position Surface form Disambiguated ID Type / Status
Subject Korean Air E30717 entity
Predicate IATAcode P418 FINISHED
Object KE
KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
 E159119 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: KE | Statement: [Korean Air, IATAcode, KE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KE
Context triple: [Korean Air, IATAcode, KE]
  • A. KE
    KE is the two-letter ISO 3166-1 alpha-2 country code assigned to Kenya for international identification and data standards.
  • B. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • C. KO
    KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • 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. KY
    KY is the postcode area covering Kirkcaldy and surrounding parts of eastern Scotland.
  • 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: KE
Triple: [Korean Air, IATAcode, KE]
Generated description
KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KE
Target entity description: KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
  • A. KE
    KE is the two-letter ISO 3166-1 alpha-2 country code assigned to Kenya for international identification and data standards.
  • B. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • C. KO
    KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • 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. KY
    KY is the postcode area covering Kirkcaldy and surrounding parts of eastern Scotland.
  • 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_69a498fd4e408190bd73eca30ea9754c completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c382b6588190833c39ac84fb6139 completed March 1, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde353b148190b9122f1d6d80fbd4 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acdea5150c8190ab248df8852bcde6 completed March 8, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_69acdefd76708190be68b157e83cfd87 completed March 8, 2026, 2:29 a.m.
Created at: March 1, 2026, 7:59 p.m.