Triple
T36212025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shin-Hotaka Ropeway |
E1047577
|
entity |
| Predicate | totalVerticalInterval |
P10733
|
FINISHED |
| Object | about 1039 meters |
—
|
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: about 1039 meters | Statement: [Shin-Hotaka Ropeway, totalVerticalInterval, about 1039 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalVerticalInterval Context triple: [Shin-Hotaka Ropeway, totalVerticalInterval, about 1039 meters]
-
A.
verticalExtent
chosen
Indicates the total height or vertical span of an entity or region from its lowest to highest point.
-
B.
targetVertical
Indicates that one entity is directed toward, aligned with, or intended for a specific vertical market, domain, or industry segment.
-
C.
verticalLocation
Indicates a vertical positional relationship where one entity is located above or below another along the up-down axis.
-
D.
totalHeight
Indicates the combined vertical measurement resulting from adding the heights of one or more entities.
-
E.
verticalLiftSpanLength
Indicates the length of the span that moves vertically in a lifting structure or mechanism.
- 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_69f76e4214748190a76c986d2a1838c2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:09 p.m.