Triple
T8746042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Ridge route |
E207829
|
entity |
| Predicate | typicalSnowDifficulty |
P85159
|
FINISHED |
| Object | up to 50 degrees |
—
|
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: up to 50 degrees | Statement: [North Ridge route, typicalSnowDifficulty, up to 50 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSnowDifficulty Context triple: [North Ridge route, typicalSnowDifficulty, up to 50 degrees]
-
A.
snowQuality
Indicates the condition or characteristics of the snow, such as its texture, depth, or suitability for a particular use.
-
B.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
C.
hasSnowType
Indicates that something possesses or is characterized by a particular type or category of snow.
-
D.
featuresSnowEffects
Indicates that something includes or displays visual or environmental effects related to falling or accumulated snow.
-
E.
hasSnowOccasionally
Indicates that the subject experiences snowfall at irregular or infrequent intervals rather than regularly or never.
- F. None of above. chosen
Provenance (4 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_69ca835bb2bc819084bb5906cb6ef7f8 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d745e0081909cab216593d5c01b |
completed | March 31, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69cc5c160dac8190b4aeb4bf0529de52 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:39 p.m.