Triple
T33077077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | スカイライナー |
E846393
|
entity |
| Predicate | 関連列車種別 |
P56947
|
FINISHED |
| Object | アクセス特急 |
—
|
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: アクセス特急 | Statement: [スカイライナー, 関連列車種別, アクセス特急]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連列車種別 Context triple: [スカイライナー, 関連列車種別, アクセス特急]
-
A.
trainTypeUsed
chosen
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
B.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
-
C.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
D.
usesTrainNumber
Indicates that one entity operates, identifies, or references another entity by a specific train number.
-
E.
relatedRollingStock
Indicates a relationship between pieces of rolling stock that are associated with each other, such as through shared operations, configurations, or functional linkage.
- 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:25 a.m.