Triple

T1984139
Position Surface form Disambiguated ID Type / Status
Subject Chautauqua Airlines E43100 entity
Predicate IATA code P2569 FINISHED
Object RP
RP is the former IATA airline designator assigned to Chautauqua Airlines, a now-defunct regional carrier in the United States.
 E223147 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: RP | Statement: [Chautauqua Airlines, IATA code, RP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RP
Context triple: [Chautauqua Airlines, IATA code, RP]
  • A. RP
    RP is the prestige British English accent traditionally associated with educated speakers and national broadcasters in the United Kingdom.
  • B. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • C. R
    R is a New York City Subway service that runs along the Broadway Line in Manhattan and Queens, providing local transit through key commercial and residential areas.
  • D. R
    R is a widely used open-source programming language and environment focused on statistical computing, data analysis, and graphical visualization.
  • E. RB
    RB is the abbreviation for CERN’s Research Board, the committee responsible for overseeing and approving the laboratory’s scientific research program.
  • 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: RP
Triple: [Chautauqua Airlines, IATA code, RP]
Generated description
RP is the former IATA airline designator assigned to Chautauqua Airlines, a now-defunct regional carrier in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RP
Target entity description: RP is the former IATA airline designator assigned to Chautauqua Airlines, a now-defunct regional carrier in the United States.
  • A. RP
    RP is the prestige British English accent traditionally associated with educated speakers and national broadcasters in the United Kingdom.
  • B. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • C. R
    R is a New York City Subway service that runs along the Broadway Line in Manhattan and Queens, providing local transit through key commercial and residential areas.
  • D. R
    R is a widely used open-source programming language and environment focused on statistical computing, data analysis, and graphical visualization.
  • E. RB
    RB is the abbreviation for CERN’s Research Board, the committee responsible for overseeing and approving the laboratory’s scientific research program.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb820815481908aac6d89b437225b completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae03301a2481909f6147482d490b90 completed March 8, 2026, 11:16 p.m.
NEDg Description generation batch_69ae04eb6c5c8190914fc35975400784 completed March 8, 2026, 11:23 p.m.
NED2 Entity disambiguation (via description) batch_69ae055df5ec8190ae39d938a8102b9d completed March 8, 2026, 11:25 p.m.
Created at: March 4, 2026, 7:37 p.m.