Triple

T2298219
Position Surface form Disambiguated ID Type / Status
Subject Swiss International Air Lines E51666 entity
Predicate threeLetterCode P418 FINISHED
Object SWR
SWR is the three-letter airline designator used by Swiss International Air Lines in aviation operations and scheduling.
 E255261 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: SWR | Statement: [Swiss International Air Lines, threeLetterCode, SWR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SWR
Context triple: [Swiss International Air Lines, threeLetterCode, SWR]
  • A. SWR
    SWR is the National Rail station code for St Werburgh's Road railway station in Manchester, England.
  • B. SRW
    SRW (Search/Retrieve Web Service) is a web-based information retrieval protocol that modernizes and extends traditional library search standards for use over HTTP.
  • C. SWC
    SWC is the abbreviation for the Southwest Conference, a former NCAA Division I college athletic conference that primarily featured schools from Texas and the surrounding region.
  • D. SWP
    SWP is the commonly used acronym for California’s State Water Project, a massive water storage and delivery system supplying water to millions of residents and vast agricultural areas.
  • E. SWA
    SWA is the ICAO airline designator used to identify Southwest Airlines in aviation operations and air traffic control.
  • 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: SWR
Triple: [Swiss International Air Lines, threeLetterCode, SWR]
Generated description
SWR is the three-letter airline designator used by Swiss International Air Lines in aviation operations and scheduling.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SWR
Target entity description: SWR is the three-letter airline designator used by Swiss International Air Lines in aviation operations and scheduling.
  • A. SWR
    SWR is the National Rail station code for St Werburgh's Road railway station in Manchester, England.
  • B. SRW
    SRW (Search/Retrieve Web Service) is a web-based information retrieval protocol that modernizes and extends traditional library search standards for use over HTTP.
  • C. SWC
    SWC is the abbreviation for the Southwest Conference, a former NCAA Division I college athletic conference that primarily featured schools from Texas and the surrounding region.
  • D. SWP
    SWP is the commonly used acronym for California’s State Water Project, a massive water storage and delivery system supplying water to millions of residents and vast agricultural areas.
  • E. SWA
    SWA is the ICAO airline designator used to identify Southwest Airlines in aviation operations and air traffic control.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5df37808190ba6a43dc1e9e723a completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8954a804819092c716582f23af14 completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8b188f18819088eaa3866485191a completed March 9, 2026, 8:55 a.m.
NED2 Entity disambiguation (via description) batch_69ae8b83efd48190a832032775803919 completed March 9, 2026, 8:57 a.m.
Created at: March 4, 2026, 7:49 p.m.