Triple
T317296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka International Airport |
E7734
|
entity |
| Predicate | hasNoiseRegulations |
P3020
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
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: yes | Statement: [Osaka International Airport, hasNoiseRegulations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoiseRegulations Context triple: [Osaka International Airport, hasNoiseRegulations, yes]
-
A.
hasSpeedLimit
Indicates that a specified maximum allowable speed is imposed on the associated entity or context.
-
B.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
C.
regulatesUse
chosen
Indicates that one entity controls, governs, or sets rules for how another entity may be used.
-
D.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
E.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea65ca7081908093e6aaaf2d34f7 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.