Triple
T36750646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sapporo Municipal Subway 5000 series |
E907901
|
entity |
| Predicate | hasInteriorSeatingType |
P6655
|
FINISHED |
| Object | longitudinal seating |
—
|
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: longitudinal seating | Statement: [Sapporo Municipal Subway 5000 series, hasInteriorSeatingType, longitudinal seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteriorSeatingType Context triple: [Sapporo Municipal Subway 5000 series, hasInteriorSeatingType, longitudinal seating]
-
A.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
B.
hasMezzanineSeating
Indicates that a venue includes a mezzanine level where seating is provided.
-
C.
hasBermSeating
Indicates that a venue or location includes berm-style seating areas, typically grass-covered embankments where spectators can sit.
-
D.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
-
E.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for 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_69f76e76d10881909ec1679bc043108c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00c07b302081908bf9755f8fdbc36e |
completed | May 10, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_6a00bfffb168819084b65804d601896d |
completed | May 10, 2026, 5:27 p.m. |
Created at: May 3, 2026, 4:12 p.m.