Triple
T14985377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magnetic Hill |
E373687
|
entity |
| Predicate | actualSlope |
P83773
|
FINISHED |
| Object | downhill |
—
|
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: downhill | Statement: [Magnetic Hill, actualSlope, downhill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actualSlope Context triple: [Magnetic Hill, actualSlope, downhill]
-
A.
usesWeightedAverageOfSlopes
Indicates that something is determined or calculated by taking a weighted average of multiple slope values.
-
B.
usesIntermediateSlope
Indicates that an entity employs or operates on a slope of intermediate steepness as part of its process or behavior.
-
C.
isOnSlopeOf
chosen
Indicates that one entity is located on the inclined surface or side of another entity, typically a sloping terrain or structure.
-
D.
correctorSlopeComputation
Indicates the computation of the slope used in a corrector step within an iterative or numerical correction process.
-
E.
slopeUse
Indicates how a particular slope or gradient is utilized or purposed in relation to another entity.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6ff4a7c8190ab7554f3a1a09b67 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.