Triple
T16485259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergisel Stadium |
E400421
|
entity |
| Predicate | hasLandingSlopeIncline |
P25297
|
FINISHED |
| Object | approx. 34° |
—
|
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: approx. 34° | Statement: [Bergisel Stadium, hasLandingSlopeIncline, approx. 34°]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandingSlopeIncline Context triple: [Bergisel Stadium, hasLandingSlopeIncline, approx. 34°]
-
A.
hasIncline
chosen
Indicates that one entity possesses or exhibits a slope, tilt, or upward/downward angle relative to another reference.
-
B.
hasSlopeRating
Indicates that something (typically a golf course or hole) is associated with a specific slope rating value that quantifies its relative difficulty for bogey golfers compared to scratch golfers.
-
C.
isOnSlopeOf
Indicates that one entity is located on the inclined surface or side of another entity, typically a sloping terrain or structure.
-
D.
hasSettlementOnSlopes
Indicates that a settlement is located on or extends across the slopes of a landform such as a hill or mountain.
-
E.
hasBeachSlope
Indicates that a location or coastal area possesses a particular gradient or steepness of its beach surface.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e05bf448190947b9da15fd29d0a |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:13 a.m.