Triple

T27524027

Position	Surface form	Disambiguated ID	Type / Status
Subject	Japan–South Korea	`E694786`	entity
Predicate	hasAirRoute	`P105188`	FINISHED
Object	Fukuoka–Busan Fukuoka–Busan is a major international air route linking the Japanese city of Fukuoka with the South Korean port city of Busan, facilitating frequent short-haul travel and trade between the two countries.	`E1778425`	NE FINISHED

How this triple was built (3 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: Fukuoka–Busan | Statement: [Japan–South Korea, hasAirRoute, Fukuoka–Busan]

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: Fukuoka–Busan
Triple: [Japan–South Korea, hasAirRoute, Fukuoka–Busan]

Generated description

Fukuoka–Busan is a major international air route linking the Japanese city of Fukuoka with the South Korean port city of Busan, facilitating frequent short-haul travel and trade between the two countries.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: hasAirRoute
Context triple: [Japan–South Korea, hasAirRoute, Fukuoka–Busan]

A. hasAirTravelLink chosen
Indicates that there is a direct or established air travel connection (such as flights or air routes) between the related entities.
B. hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
C. hasAirportAccessTo
Indicates that one location or entity has direct access to another via an airport connection or service.
D. hasCityPair
Indicates a relationship that links two cities considered as a connected or associated pair, often for purposes such as travel, trade, or comparison.
E. airlineServiceVia
Indicates that an airline service operates between two locations with a specified intermediate stop or transit point.
F. None of above.

Provenance (6 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_69ef538550208190aa9de8e2cb260d93`	completed	April 27, 2026, 12:16 p.m.
NER	Named-entity recognition	`batch_69f6359e3d3c81909814e2f0a7fb0ea9`	completed	May 2, 2026, 5:34 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a12c5b189388190a9f0ca71c78e1eee`	completed	May 24, 2026, 9:32 a.m.
NEDg	Description generation	`batch_6a12c66d5b80819085520b64e4359900`	completed	May 24, 2026, 9:35 a.m.
NED2	Entity disambiguation (via description)	`batch_6a12c74f073c8190b84c1e5acc666bf3`	completed	May 24, 2026, 9:39 a.m.
PD	Predicate disambiguation	`batch_69f631871c888190bf29466fe4254e51`	completed	May 2, 2026, 5:16 p.m.

Created at: April 27, 2026, 1:22 p.m.