Triple
T25997614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka Municipal Subway 10 series |
E646527
|
entity |
| Predicate | hasGangwaysBetweenCars |
P26478
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Osaka Municipal Subway 10 series, hasGangwaysBetweenCars, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGangwaysBetweenCars Context triple: [Osaka Municipal Subway 10 series, hasGangwaysBetweenCars, true]
-
A.
hasGangwayAtCabEnd
Indicates that a vehicle or unit has a gangway located at its cab end, allowing passage between connected units from that end.
-
B.
hasGangway
chosen
Indicates that one entity is equipped with or connected to a gangway that provides access or passage to or from another entity.
-
C.
hasBusBays
Indicates that a location or facility is equipped with one or more designated bus bays for buses to stop, load, or unload passengers.
-
D.
hasCabAtEachEnd
Indicates that something (typically a vehicle or train) has a cab located at both of its ends.
-
E.
hasCargoAccess
Indicates that an entity has the ability or permission to access a designated cargo area or its contents.
- 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_69e77e88cb8481908da31d4a00661f55 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6057012248190a486e723fdd2107e |
completed | May 2, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 8:58 a.m.