Triple

T8887820
Position Surface form Disambiguated ID Type / Status
Subject Kansai Kūkō E211578 entity
Predicate hasTerminal P182 FINISHED
Object Terminal 2
Terminal 2 is a low-cost carrier-focused passenger terminal at Kansai International Airport in Osaka, Japan.
E48198 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: Terminal 2 | Statement: [Kansai Kūkō, hasTerminal, Terminal 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2
Context triple: [Kansai Kūkō, hasTerminal, Terminal 2]
  • A. Terminal 2
    Terminal 2 is one of the main passenger terminals at Manchester Airport, handling a large share of the airport’s international and domestic flights.
  • B. Terminal 2
    Terminal 2 is a passenger terminal at El Dorado International Airport in Bogotá, Colombia, serving specific airlines and routes within the airport’s operations.
  • C. Terminal 2
    Terminal 2 is one of the main passenger terminals at Ontario International Airport in Southern California, serving domestic airline operations and traveler services.
  • D. Terminal 2
    Terminal 2 is one of the passenger terminals at Chicago O'Hare International Airport, serving various domestic and regional flights with multiple concourses and airline operations.
  • E. Terminal 2
    Terminal 2 is a secondary passenger terminal at Lisbon’s Humberto Delgado Airport, mainly serving low-cost and regional airlines.
  • 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: Terminal 2
Triple: [Kansai Kūkō, hasTerminal, Terminal 2]
Generated description
Terminal 2 is a low-cost carrier-focused passenger terminal at Kansai International Airport in Osaka, Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Terminal 2
Target entity description: Terminal 2 is a low-cost carrier-focused passenger terminal at Kansai International Airport in Osaka, Japan.
  • A. Terminal 2 chosen
    Terminal 2 is a low-cost carrier–focused passenger terminal at Kansai International Airport in Osaka, Japan.
  • B. Terminal 2
    Terminal 2 is a major passenger terminal at Incheon International Airport in South Korea, serving as a modern hub for several international airlines.
  • C. Terminal 2
    Terminal 2 is one of the main passenger terminals at Tokyo's Haneda Airport, serving primarily domestic flights with modern facilities and amenities.
  • D. Terminal 2
    Terminal 2 is a passenger terminal at Don Mueang International Airport in Bangkok, primarily serving low-cost and domestic airline operations.
  • E. Terminal 2
    Terminal 2 is a concourse at St. Louis Lambert International Airport primarily serving low-cost and international carriers.
  • 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_69ca83907954819096d52a245b635841 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc618e58d08190be3ebcbe3701b1db completed April 1, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab821e808190a918bf787cde54b6 completed April 3, 2026, 11:58 a.m.
NEDg Description generation batch_69cfad8cb9cc81909d4df290c7411898 completed April 3, 2026, 12:07 p.m.
NED2 Entity disambiguation (via description) batch_69cfae0141b48190a443ae181a495bf6 completed April 3, 2026, 12:09 p.m.
Created at: March 30, 2026, 6:53 p.m.