Triple
T33077078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | スカイライナー |
E846393
|
entity |
| Predicate | 座席配置 |
P16826
|
FINISHED |
| Object | クロスシート中心 |
—
|
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: クロスシート中心 | Statement: [スカイライナー, 座席配置, クロスシート中心]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 座席配置 Context triple: [スカイライナー, 座席配置, クロスシート中心]
-
A.
seatingConfiguration
chosen
Indicates how seats are arranged or organized relative to each other in a given context.
-
B.
seatForm
Indicates that one entity serves as the physical seating structure or configuration associated with another entity.
-
C.
seatStructure
Indicates that one entity serves as the structural or physical seating component or arrangement associated with another entity.
-
D.
seatDistributionCharacteristic
Indicates how seats are allocated or arranged according to specific rules, patterns, or properties within a given context.
-
E.
seatDistributionDeterminedBy
Indicates that the allocation of seats (e.g., in a body or venue) is decided or governed according to a specified rule, factor, or authority.
- 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.