Triple
T19478588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loveland Ski Area |
E487317
|
entity |
| Predicate | terrainDifficultyDistribution |
P43109
|
FINISHED |
| Object | beginner, intermediate, advanced, expert |
—
|
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, intermediate, advanced, expert | Statement: [Loveland Ski Area, terrainDifficultyDistribution, beginner, intermediate, advanced, expert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainDifficultyDistribution Context triple: [Loveland Ski Area, terrainDifficultyDistribution, beginner, intermediate, advanced, expert]
-
A.
hasTrailDifficulty
Indicates the level of challenge or effort required to traverse a particular trail or route.
-
B.
hasBeginnerTerrain
chosen
Indicates that something provides or includes terrain or areas suitable for beginners.
-
C.
difficultyClassRange
Indicates the range of difficulty classes within which an action, task, or challenge is considered to fall.
-
D.
difficultySource
Indicates that one entity is the cause, origin, or contributing factor to the difficulty or challenge experienced in relation to another entity or situation.
-
E.
difficultyRelativeToOtherRoutes
Indicates how the difficulty level of one route compares relative to other routes.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63437b9748190a8fc6bf6b3d90918 |
completed | April 20, 2026, 2:12 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7883308190b73912a71a35a835 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:39 p.m.