Triple

T10161018
Position Surface form Disambiguated ID Type / Status
Subject Sultan Mahmud Airport E233889 entity
Predicate IATAcode P418 FINISHED
Object TGG
TGG is the IATA airport code for Sultan Mahmud Airport, which serves Kuala Terengganu in Malaysia.
E845525 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: TGG | Statement: [Sultan Mahmud Airport, IATAcode, TGG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TGG
Context triple: [Sultan Mahmud Airport, IATAcode, TGG]
  • A. ZGGG
    ZGGG is the ICAO airport code for Guangzhou Baiyun International Airport, a major aviation hub serving Guangzhou in southern China.
  • B. GGC
    GGC is the abbreviation for the Gulf of Guinea Commission, a regional organization that promotes cooperation and security among states bordering the Gulf of Guinea in West and Central Africa.
  • C. DGG
    DGG is the station code for Dungog railway station in New South Wales, Australia.
  • D. KGG
    KGG is the abbreviated name of Kings Guard Gaming, an NBA 2K League esports team affiliated with the Sacramento Kings.
  • E. TGR
    TGR is the acronym for Chile’s Tesorería General de la República, the public institution responsible for managing and safeguarding the central government’s financial resources and tax revenues.
  • 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: TGG
Triple: [Sultan Mahmud Airport, IATAcode, TGG]
Generated description
TGG is the IATA airport code for Sultan Mahmud Airport, which serves Kuala Terengganu in Malaysia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TGG
Target entity description: TGG is the IATA airport code for Sultan Mahmud Airport, which serves Kuala Terengganu in Malaysia.
  • A. ZGGG
    ZGGG is the ICAO airport code for Guangzhou Baiyun International Airport, a major aviation hub serving Guangzhou in southern China.
  • B. GGC
    GGC is the abbreviation for the Gulf of Guinea Commission, a regional organization that promotes cooperation and security among states bordering the Gulf of Guinea in West and Central Africa.
  • C. DGG
    DGG is the station code for Dungog railway station in New South Wales, Australia.
  • D. KGG
    KGG is the abbreviated name of Kings Guard Gaming, an NBA 2K League esports team affiliated with the Sacramento Kings.
  • E. TGR
    TGR is the acronym for Chile’s Tesorería General de la República, the public institution responsible for managing and safeguarding the central government’s financial resources and tax revenues.
  • 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_69ca848e80748190b91d1e04d35512c7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec59b01081908be6ca37dc575465 completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300c2651c8190a80c933002ac62e8 completed April 6, 2026, 12:39 a.m.
NEDg Description generation batch_69d30254aabc8190966a4398c59a851e completed April 6, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69d30305924c8190998cbefa372dca9a completed April 6, 2026, 12:49 a.m.
Created at: March 30, 2026, 9:09 p.m.