Triple
T37749872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JR Kyushu Jet Ferry |
E940949
|
entity |
| Predicate | serviceSpeedType |
P184108
|
FINISHED |
| Object | high-speed |
—
|
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: high-speed | Statement: [JR Kyushu Jet Ferry, serviceSpeedType, high-speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceSpeedType Context triple: [JR Kyushu Jet Ferry, serviceSpeedType, high-speed]
-
A.
serviceSpeedRelativeToLocal
Indicates how the speed or promptness of a service compares to the typical or average service speed in the local area.
-
B.
hasServiceSpeed
Indicates that an entity provides a service operating at a specified speed or performance rate.
-
C.
designedServiceSpeed
Indicates the intended or specified operational speed at which a service is designed to function.
-
D.
speedupType
Indicates the kind or category of performance improvement achieved relative to a baseline.
-
E.
speedDescribedAs
chosen
Indicates that one entity characterizes or labels the speed of another entity using a particular description or term.
- 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_69f76ee1f3a88190834e6c8af99bccc9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd8ccbd4c88190b13aae0673b3c821 |
completed | May 8, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69fd8ae2227c819089546f5c3629799e |
completed | May 8, 2026, 7:04 a.m. |
Created at: May 3, 2026, 4:19 p.m.