Triple
T12486856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowdon Ranger Path |
E298455
|
entity |
| Predicate | gradient |
P54393
|
FINISHED |
| Object | relatively steady |
—
|
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: relatively steady | Statement: [Snowdon Ranger Path, gradient, relatively steady]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gradient Context triple: [Snowdon Ranger Path, gradient, relatively steady]
-
A.
averageGradient
chosen
Indicates the mean rate of change (slope) of a quantity over a specified interval or region.
-
B.
maximumGradient
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
-
C.
slopeUse
Indicates how a particular slope or gradient is utilized or purposed in relation to another entity.
-
D.
acceleratingGradient
Indicates that a process, change, or effect is increasing in rate over time, becoming progressively faster or more intense.
-
E.
differential
Indicates a relationship where one quantity or state is defined as the infinitesimal change or difference relative to another variable or function.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.