Triple

T17684976
Position Surface form Disambiguated ID Type / Status
Subject King Mswati III International Airport E440864 entity
Predicate ICAOcode P419 FINISHED
Object FDSK
FDSK is the ICAO airport code for King Mswati III International Airport, the main international gateway to Eswatini.
E1282886 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: FDSK | Statement: [King Mswati III International Airport, ICAOcode, FDSK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FDSK
Context triple: [King Mswati III International Airport, ICAOcode, FDSK]
  • A. DSK
    DSK is the IATA airport code for Dera Ismail Khan Airport in Pakistan.
  • B. FDS
    FDS is the onboard computer system on NASA’s Voyager 1 spacecraft responsible for managing instruments and formatting data for transmission back to Earth.
  • C. FDS
    FDS is the vehicle registration code for the district of Freudenstadt in the German state of Baden-Württemberg.
  • D. FDS
    FDS is a prestigious postgraduate professional qualification in dentistry awarded by certain Royal Colleges and dental institutions.
  • E. FKS
    FKS is the common abbreviation for FK Sarajevo, a professional football club based in Sarajevo, Bosnia and Herzegovina.
  • 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: FDSK
Triple: [King Mswati III International Airport, ICAOcode, FDSK]
Generated description
FDSK is the ICAO airport code for King Mswati III International Airport, the main international gateway to Eswatini.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: FDSK
Target entity description: FDSK is the ICAO airport code for King Mswati III International Airport, the main international gateway to Eswatini.
  • A. DSK
    DSK is the IATA airport code for Dera Ismail Khan Airport in Pakistan.
  • B. FDS
    FDS is the onboard computer system on NASA’s Voyager 1 spacecraft responsible for managing instruments and formatting data for transmission back to Earth.
  • C. FDS
    FDS is the vehicle registration code for the district of Freudenstadt in the German state of Baden-Württemberg.
  • D. FDS
    FDS is a prestigious postgraduate professional qualification in dentistry awarded by certain Royal Colleges and dental institutions.
  • E. FKS
    FKS is the common abbreviation for FK Sarajevo, a professional football club based in Sarajevo, Bosnia and Herzegovina.
  • 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4704710488190826aaf0bdd4b2088 completed April 19, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02232c47f481909b0ac8f278b0144b completed May 11, 2026, 6:42 p.m.
NEDg Description generation batch_6a0224d356748190aac87f7bc6a12ee7 completed May 11, 2026, 6:49 p.m.
NED2 Entity disambiguation (via description) batch_6a02258d6db881908a80b23b5d44cf98 completed May 11, 2026, 6:53 p.m.
Created at: April 10, 2026, 10:02 a.m.