Triple
T25135591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seibu 40000 series |
E629646
|
entity |
| Predicate | seatingFeature |
P16826
|
FINISHED |
| Object | transverse-style seat arrangement in some configurations |
—
|
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: transverse-style seat arrangement in some configurations | Statement: [Seibu 40000 series, seatingFeature, transverse-style seat arrangement in some configurations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatingFeature Context triple: [Seibu 40000 series, seatingFeature, transverse-style seat arrangement in some configurations]
-
A.
seatFeature
Indicates that a seat possesses or is equipped with a particular feature or characteristic.
-
B.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
C.
seatingConfiguration
chosen
Indicates how seats are arranged or organized relative to each other in a given context.
-
D.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
E.
seatingPosition
Indicates the relative location or arrangement of an entity’s seat with respect to other seats or a reference point in a seating layout.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f465febf508190a350d9e1f9b4dda5 |
completed | May 1, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:29 a.m.