Triple
T16802285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Hirafu |
E408386
|
entity |
| Predicate | typicalSnowQuality |
P69359
|
FINISHED |
| Object | light dry powder |
—
|
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: light dry powder | Statement: [Grand Hirafu, typicalSnowQuality, light dry powder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSnowQuality Context triple: [Grand Hirafu, typicalSnowQuality, light dry powder]
-
A.
typicalSnowDifficulty
Indicates the usual or characteristic level of difficulty associated with snow conditions for an activity, route, or location.
-
B.
snowQuality
chosen
Indicates the condition or characteristics of the snow, such as its texture, depth, or suitability for a particular use.
-
C.
hasSnowOccasionally
Indicates that the subject experiences snowfall at irregular or infrequent intervals rather than regularly or never.
-
D.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
E.
hasSnowType
Indicates that something possesses or is characterized by a particular type or category of snow.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2c8fe58819087d3b83635255c34 |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.