Triple
T24986400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokushima Awaodori Airport |
E625319
|
entity |
| Predicate | providesAirAccessTo |
P150937
|
FINISHED |
| Object | Tokushima Prefecture |
—
|
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: Tokushima Prefecture | Statement: [Tokushima Awaodori Airport, providesAirAccessTo, Tokushima Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesAirAccessTo Context triple: [Tokushima Awaodori Airport, providesAirAccessTo, Tokushima Prefecture]
-
A.
hasAirportAccessTo
chosen
Indicates that one location or entity has direct access to another via an airport connection or service.
-
B.
hasRunwaysAt
Indicates that a location or facility possesses one or more runways situated at that place.
-
C.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
-
D.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
E.
servesPassengerTrafficTo
Indicates that a transportation facility or service provides regular passenger traffic access or operations to a particular location or area.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 6:03 a.m.