Triple
T34649994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Izumisano |
E889808
|
entity |
| Predicate | airportLocatedOnArtificialIsland |
P139617
|
FINISHED |
| Object | Kansai International Airport |
—
|
NE NERFINISHED |
How this triple was built (2 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: Kansai International Airport | Statement: [Izumisano, airportLocatedOnArtificialIsland, Kansai International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportLocatedOnArtificialIsland Context triple: [Izumisano, airportLocatedOnArtificialIsland, Kansai International Airport]
-
A.
locatedOnArtificialIsland
chosen
Indicates that an entity is situated on an island that has been artificially constructed rather than naturally formed.
-
B.
airportIsland
Indicates that an airport is located on, or associated with, an island.
-
C.
airportServesAtoll
Indicates that an airport provides transportation services to, or primarily serves, a specific atoll.
-
D.
airportLocatedIn
Indicates that an airport is geographically situated within a specific administrative or territorial area.
-
E.
isMajorAirportOnIsland
Indicates that the airport is classified as a major airport and is geographically located on an island.
- F. None of above.
Provenance (3 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_69f349d825c88190bfc6170ac9281260 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72ad38a208190b4bdc828297f86ad |
completed | May 3, 2026, 11 a.m. |
| PD | Predicate disambiguation | batch_69f72a0243988190a43b8ea22457cd30 |
completed | May 3, 2026, 10:57 a.m. |
Created at: May 1, 2026, 2:04 a.m.