Triple
T25350678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buck Hill |
E635672
|
entity |
| Predicate | hasRunDifficultyRange |
P124063
|
FINISHED |
| Object | beginner to advanced runs |
—
|
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: beginner to advanced runs | Statement: [Buck Hill, hasRunDifficultyRange, beginner to advanced runs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunDifficultyRange Context triple: [Buck Hill, hasRunDifficultyRange, beginner to advanced runs]
-
A.
hasRunDifficultyDistribution
Indicates that there is an associated distribution describing how difficult different runs or executions of a process or activity are.
-
B.
hasDifficultyClass
chosen
Indicates that something (such as a task, challenge, or problem) is associated with a specific level of difficulty or complexity.
-
C.
hasMeasurementDifficulty
Indicates that performing a measurement on something is challenging or problematic in some way.
-
D.
hasDifficultyEffect
Indicates that one entity causes a change in the difficulty level or challenge associated with another entity or activity.
-
E.
hasDifficultyContext
Indicates that something’s difficulty is defined, interpreted, or constrained within a particular situational or contextual framework.
- 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_69e75a9ac5d881909387ed766e20cd47 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f49dfb8c688190aad99932e6fe956a |
completed | May 1, 2026, 12:35 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 1:34 p.m.