Triple

T73982
Position Surface form Disambiguated ID Type / Status
Subject IEEE/AIAA Digital Avionics Systems Conference E1481 entity
Predicate hasAbbreviation P43 FINISHED
Object DASC
DASC is a leading annual technical conference focused on digital avionics systems, organized jointly by IEEE and AIAA.
E6190 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: DASC | Statement: [IEEE/AIAA Digital Avionics Systems Conference, hasAbbreviation, DASC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DASC
Context triple: [IEEE/AIAA Digital Avionics Systems Conference, hasAbbreviation, DASC]
  • A. DCA
    DCA is the three-letter IATA airport code for Ronald Reagan Washington National Airport, the primary domestic airport serving Washington, D.C.
  • B. DELTA
    DELTA is the radio callsign used by pilots and air traffic control to identify and communicate with Delta Air Lines flights.
  • C. SAS
    SAS is the School of Arts and Sciences at the University of Pennsylvania, encompassing the university’s core liberal arts and sciences departments and programs.
  • D. DNI
    DNI is the commonly used acronym for the Director of National Intelligence, the head of the U.S. intelligence community.
  • E. DL
    DL is the two-letter IATA airline designator used to identify Delta Air Lines on tickets, schedules, and flight information.
  • 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: DASC
Triple: [IEEE/AIAA Digital Avionics Systems Conference, hasAbbreviation, DASC]
Generated description
DASC is a leading annual technical conference focused on digital avionics systems, organized jointly by IEEE and AIAA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: DASC
Target entity description: DASC is a leading annual technical conference focused on digital avionics systems, organized jointly by IEEE and AIAA.
  • A. DESE
    DESE is the state agency responsible for overseeing public elementary and secondary education in Massachusetts, including standards, accountability, and school support.
  • B. DCA
    DCA (Defense Communications Agency) was a U.S. Department of Defense organization responsible for managing and overseeing military communications networks, including early internet precursor systems.
  • C. DCA
    DCA is the three-letter IATA airport code for Ronald Reagan Washington National Airport, the primary domestic airport serving Washington, D.C.
  • D. DELTA
    DELTA is the radio callsign used by pilots and air traffic control to identify and communicate with Delta Air Lines flights.
  • E. DART Victory Station
    DART Victory Station is a Dallas Area Rapid Transit rail station serving the Victory Park area, including major venues like the American Airlines Center.
  • 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_69a24c06b3bc8190aa4ac89026115efc completed Feb. 28, 2026, 1:59 a.m.
NER Named-entity recognition batch_69a24f1a352081909cfa257202178ed6 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2554ffb8c8190a30aceecd7f30d96 completed Feb. 28, 2026, 2:39 a.m.
NEDg Description generation batch_69a25943cba88190a78f708d453ce968 completed Feb. 28, 2026, 2:56 a.m.
NED2 Entity disambiguation (via description) batch_69a259c2706c8190b5319c004e207c29 completed Feb. 28, 2026, 2:58 a.m.
Created at: Feb. 28, 2026, 2:03 a.m.