Triple

T8505220
Position Surface form Disambiguated ID Type / Status
Subject Tulsa International Airport E201316 entity
Predicate IATAcode P418 FINISHED
Object TUL
TUL is the three-letter IATA airport code for Tulsa International Airport, a commercial and military airfield serving Tulsa, Oklahoma.
 E739361 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: TUL | Statement: [Tulsa International Airport, IATAcode, TUL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TUL
Context triple: [Tulsa International Airport, IATAcode, TUL]
  • A. TOL
    TOL is the standard abbreviation for the Toledo Walleye, a professional minor league ice hockey team based in Toledo, Ohio.
  • B. TOL
    TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
  • C. Tulunan
    Tulunan is a rural municipality in the province of North Cotabato on the island of Mindanao in the Philippines, known primarily for its agricultural economy.
  • D. Tus
    Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
  • E. Tu
    Tu Youyou is a Chinese pharmaceutical chemist and Nobel laureate renowned for discovering the antimalarial drug artemisinin.
  • 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: TUL
Triple: [Tulsa International Airport, IATAcode, TUL]
Generated description
TUL is the three-letter IATA airport code for Tulsa International Airport, a commercial and military airfield serving Tulsa, Oklahoma.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TUL
Target entity description: TUL is the three-letter IATA airport code for Tulsa International Airport, a commercial and military airfield serving Tulsa, Oklahoma.
  • A. TOL
    TOL is the standard abbreviation for the Toledo Walleye, a professional minor league ice hockey team based in Toledo, Ohio.
  • B. TOL
    TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
  • C. Tulunan
    Tulunan is a rural municipality in the province of North Cotabato on the island of Mindanao in the Philippines, known primarily for its agricultural economy.
  • D. Tus
    Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
  • E. Tu
    Tu Youyou is a Chinese pharmaceutical chemist and Nobel laureate renowned for discovering the antimalarial drug artemisinin.
  • 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_69ca831fe47c8190b5c57b456d2aefa0 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5d8b7208190b199c56bf366c692 completed March 31, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e3037e4819090677c7dc607e8f2 completed April 2, 2026, 11:08 a.m.
NEDg Description generation batch_69ce4ff88ff48190a5641635187a9e4f completed April 2, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69ce50fd3150819097562093bee78a6d completed April 2, 2026, 11:20 a.m.
Created at: March 30, 2026, 6:14 p.m.