Triple
T16696065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryukyu Air Commuter |
E405718
|
entity |
| Predicate | focusesOnRouteType |
P13326
|
FINISHED |
| Object | inter-island routes |
—
|
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: inter-island routes | Statement: [Ryukyu Air Commuter, focusesOnRouteType, inter-island routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnRouteType Context triple: [Ryukyu Air Commuter, focusesOnRouteType, inter-island routes]
-
A.
includesRouteType
Indicates that one entity’s set of routes contains or covers a specific type or category of route associated with another entity.
-
B.
parentRouteType
Indicates that one route type serves as the parent or higher-level category for another route type within a route hierarchy.
-
C.
notableRouteType
Indicates that a route is particularly significant or well-known for a specific type or category (e.g., scenic, historic, commercial).
-
D.
hasRouteType
chosen
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
E.
usesRoutingType
Indicates that one entity employs or operates according to a specific routing type or routing method associated with another entity.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37eadc35881909fb0cc405a0e2fae |
completed | April 18, 2026, 12:53 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.