Triple
T21947362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merkurbergbahn funicular |
E541967
|
entity |
| Predicate | verticalInterval |
P128997
|
FINISHED |
| Object | about 381 m |
—
|
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 381 m | Statement: [Merkurbergbahn funicular, verticalInterval, about 381 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: verticalInterval Context triple: [Merkurbergbahn funicular, verticalInterval, about 381 m]
-
A.
verticalExtent
Indicates the total height or vertical span of an entity or region from its lowest to highest point.
-
B.
verticalLocation
Indicates a vertical positional relationship where one entity is located above or below another along the up-down axis.
-
C.
verticalOrder
Indicates that one entity is positioned directly above or below another along a vertical axis, establishing their relative vertical arrangement.
-
D.
verticalDrop_m
chosen
Indicates the vertical distance, measured in meters, through which something drops or falls from a higher point to a lower point.
-
E.
targetVertical
Indicates that one entity is directed toward, aligned with, or intended for a specific vertical market, domain, or industry segment.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12428dee48190acb63051ed7cd03e |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:57 p.m.