Triple
T19841186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hahnenkamm downhill race |
E476731
|
entity |
| Predicate | verticalDropApprox |
P109849
|
FINISHED |
| Object | 860 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: 860 m | Statement: [Hahnenkamm downhill race, verticalDropApprox, 860 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: verticalDropApprox Context triple: [Hahnenkamm downhill race, verticalDropApprox, 860 m]
-
A.
verticalDrop_m
Indicates the vertical distance, measured in meters, through which something drops or falls from a higher point to a lower point.
-
B.
verticalDrop_ft
Indicates the vertical distance, measured in feet, that one entity drops or falls relative to another reference level.
-
C.
dropHeight
Indicates the vertical distance from which an object is released or allowed to fall.
-
D.
approximateDrop
chosen
Indicates an estimated or roughly calculated decrease in a quantity, value, or level rather than an exact measured drop.
-
E.
secondDropHeight
Indicates the height at which an object is dropped for the second time in a sequence of drops.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6580576748190b85e234b01209ae7 |
completed | April 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e537e21d2881909b1be82f02b99d40 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.