Triple
T34267836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Sabalan |
E879220
|
entity |
| Predicate | hasPerennialSnow |
P190148
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mount Sabalan, hasPerennialSnow, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerennialSnow Context triple: [Mount Sabalan, hasPerennialSnow, yes]
-
A.
permanentSnowAndIce
chosen
Indicates that an area is persistently covered by snow and ice throughout the year, without significant seasonal melting.
-
B.
hasGlacier
Indicates that one entity possesses, contains, or is characterized by the presence of a glacier.
-
C.
hasSeasonalSnowCover
Indicates that an entity is covered by snow during certain seasons or periods of the year, rather than permanently.
-
D.
hasPermafrost
Indicates that a location or area contains ground that remains continuously frozen (permafrost) for an extended period.
-
E.
hasSnowAtHighElevations
Indicates that snow is present in areas located at higher elevations within a given region 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_69f349b4f5fc819094b441d18e95e5f1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 1, 2026, 1:56 a.m.