Triple
T34626533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakone Tozan Bus |
E889151
|
entity |
| Predicate | supportsLocalMobility |
P143272
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hakone Tozan Bus, supportsLocalMobility, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLocalMobility Context triple: [Hakone Tozan Bus, supportsLocalMobility, yes]
-
A.
supportsMobilityBetween
Indicates that one entity enables, facilitates, or allows movement or travel between two or more other entities or locations.
-
B.
supportsMobilityFeature
chosen
Indicates that an entity provides or enables a mobility-related capability or feature for another entity.
-
C.
supportsMobilityType
Indicates that one entity provides compatibility with, or can function using, a specified type of mobility or movement mode.
-
D.
supportsLocation
Indicates that one entity provides the necessary structure, foundation, or capacity to hold, host, or accommodate another entity at a particular place or position.
-
E.
hasLocalSupport
Indicates that an entity receives backing, endorsement, or assistance from people or organizations within its immediate geographic or community area.
- 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_69f349d64a388190a013cfa9bd33fad7 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:04 a.m.