Triple
T2272018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Mountain Peak |
E50680
|
entity |
| Predicate | hikingDifficulty |
P24163
|
FINISHED |
| Object | moderate to strenuous |
—
|
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: moderate to strenuous | Statement: [Blue Mountain Peak, hikingDifficulty, moderate to strenuous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hikingDifficulty Context triple: [Blue Mountain Peak, hikingDifficulty, moderate to strenuous]
-
A.
hasTrailDifficulty
chosen
Indicates the level of challenge or effort required to traverse a particular trail or route.
-
B.
hikeLength
Indicates the distance or duration associated with a hiking activity or trail.
-
C.
altitudeCategory
Indicates the classification of something based on its height or elevation relative to a reference level (e.g., low, medium, high altitude).
-
D.
totalAscent
Indicates the total cumulative elevation gained over the course of a movement, route, or activity.
-
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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.