Triple

T2498538
Position Surface form Disambiguated ID Type / Status
Subject Asiana Airlines E52407 entity
Predicate ICAOcode P419 FINISHED
Object AAR
AAR is the ICAO airline designator used to identify Asiana Airlines in international aviation operations and communications.
 E273260 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: AAR | Statement: [Asiana Airlines, ICAOcode, AAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AAR
Context triple: [Asiana Airlines, ICAOcode, AAR]
  • A. AAR
    AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
  • B. AEARU
    AEARU (Association of East Asian Research Universities) is a consortium of leading research-intensive universities in East Asia that promotes academic collaboration and exchange among its member institutions.
  • C. ARL
    ARL (Australian Rugby League) was the top-level rugby league competition in Australia during the mid-1990s, preceding the formation of the National Rugby League (NRL).
  • D. AA
    AA is the two-letter IATA airline designator used to identify American Airlines in flight schedules, tickets, and aviation systems.
  • E. AA
    AA was the common abbreviation for the German Foreign Office (Auswärtiges Amt) during the Nazi era.
  • 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: AAR
Triple: [Asiana Airlines, ICAOcode, AAR]
Generated description
AAR is the ICAO airline designator used to identify Asiana Airlines in international aviation operations and communications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AAR
Target entity description: AAR is the ICAO airline designator used to identify Asiana Airlines in international aviation operations and communications.
  • A. AAR
    AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
  • B. AEARU
    AEARU (Association of East Asian Research Universities) is a consortium of leading research-intensive universities in East Asia that promotes academic collaboration and exchange among its member institutions.
  • C. ARL
    ARL (Australian Rugby League) was the top-level rugby league competition in Australia during the mid-1990s, preceding the formation of the National Rugby League (NRL).
  • D. AA
    AA is the two-letter IATA airline designator used to identify American Airlines in flight schedules, tickets, and aviation systems.
  • E. AA
    AA was the common abbreviation for the German Foreign Office (Auswärtiges Amt) during the Nazi era.
  • 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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1ae9040819091b3ca5b98659e99 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f9ed13c81909856db636bfb2e9e completed March 9, 2026, 7:29 p.m.
NEDg Description generation batch_69af23a305a48190b457b1b66779b90d completed March 9, 2026, 7:46 p.m.
NED2 Entity disambiguation (via description) batch_69af240855848190947190a662745b77 completed March 9, 2026, 7:48 p.m.
Created at: March 6, 2026, 9:46 p.m.