Triple

T43175
Position Surface form Disambiguated ID Type / Status
Subject Delta Air Lines E848 entity
Predicate ICAOCode P419 FINISHED
Object DAL
DAL is the ICAO airline designator used to identify Delta Air Lines in aviation operations and air traffic control communications.
 E2371 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: DAL | Statement: [Delta Air Lines, ICAOCode, DAL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DAL
Context triple: [Delta Air Lines, ICAOCode, DAL]
  • A. DL
    DL is the two-letter IATA airline designator used to identify Delta Air Lines on tickets, schedules, and flight information.
  • B. DELTA
    DELTA is the radio callsign used by pilots and air traffic control to identify and communicate with Delta Air Lines flights.
  • C. ARC
    ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
  • D. DCA
    DCA is the three-letter IATA airport code for Ronald Reagan Washington National Airport, the primary domestic airport serving Washington, D.C.
  • E. DOT
    DOT is the commonly used acronym for the United States Department of Transportation, the federal agency responsible for national transportation policy and infrastructure.
  • 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: DAL
Triple: [Delta Air Lines, ICAOCode, DAL]
Generated description
DAL is the ICAO airline designator used to identify Delta Air Lines in aviation operations and air traffic control communications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DAL
Target entity description: DAL is the ICAO airline designator used to identify Delta Air Lines in aviation operations and air traffic control communications.
  • A. DL
    DL is the two-letter IATA airline designator used to identify Delta Air Lines on tickets, schedules, and flight information.
  • B. DELTA chosen
    DELTA is the radio callsign used by pilots and air traffic control to identify and communicate with Delta Air Lines flights.
  • C. ARC
    ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
  • D. DCA
    DCA is the three-letter IATA airport code for Ronald Reagan Washington National Airport, the primary domestic airport serving Washington, D.C.
  • E. DOT
    DOT is the commonly used acronym for the United States Department of Transportation, the federal agency responsible for national transportation policy and infrastructure.
  • F. None of above.

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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ae236548190bd225d125f23e6c7 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a255338b6c8190bb31101691ce689a completed Feb. 28, 2026, 2:38 a.m.
NEDg Description generation batch_69a255ef9b1081909fe71530250bd68b completed Feb. 28, 2026, 2:41 a.m.
NED2 Entity disambiguation (via description) batch_69a256c673748190abb6b556701b4a2a completed Feb. 28, 2026, 2:45 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.