Triple
T11946160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banski Suhodol |
E284302
|
entity |
| Predicate | snowCoverDuration |
P82171
|
FINISHED |
| Object | late autumn to late spring |
—
|
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: late autumn to late spring | Statement: [Banski Suhodol, snowCoverDuration, late autumn to late spring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: snowCoverDuration Context triple: [Banski Suhodol, snowCoverDuration, late autumn to late spring]
-
A.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
B.
hasSeasonalSnowCover
chosen
Indicates that an entity is covered by snow during certain seasons or periods of the year, rather than permanently.
-
C.
summitIceCover
Indicates the extent or presence of ice covering the summit of a geographic feature.
-
D.
snowQuality
Indicates the condition or characteristics of the snow, such as its texture, depth, or suitability for a particular use.
-
E.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903456ec0819082b8b10755a6b732 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.