Triple
T1193490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boreal Mountain California |
E25614
|
entity |
| Predicate | hasDifficultyRange |
P24163
|
FINISHED |
| Object | beginner to intermediate |
—
|
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 intermediate | Statement: [Boreal Mountain California, hasDifficultyRange, beginner to intermediate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifficultyRange Context triple: [Boreal Mountain California, hasDifficultyRange, beginner to intermediate]
-
A.
difficulty
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
-
B.
hasMeasurementDifficulty
Indicates that performing a measurement on something is challenging or problematic in some way.
-
C.
hasTrailDifficulty
chosen
Indicates the level of challenge or effort required to traverse a particular trail or route.
-
D.
difficultyRelativeTo
Indicates that one entity’s level of difficulty is being compared to and expressed in relation to another entity’s level of difficulty.
-
E.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd7743548190a70d3f3c7378aaa7 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.