Triple
T21283752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baldwin Lake |
E524596
|
entity |
| Predicate | snowInfluence |
P143596
|
FINISHED |
| Object | receives snowmelt from surrounding mountains |
—
|
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: receives snowmelt from surrounding mountains | Statement: [Baldwin Lake, snowInfluence, receives snowmelt from surrounding mountains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: snowInfluence Context triple: [Baldwin Lake, snowInfluence, receives snowmelt from surrounding mountains]
-
A.
snowQuality
Indicates the condition or characteristics of the snow, such as its texture, depth, or suitability for a particular use.
-
B.
snowAccumulation
Indicates that snow has collected or built up on a surface or in a location over time.
-
C.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
D.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
E.
featuresSnowEffects
Indicates that something includes or displays visual or environmental effects related to falling or accumulated snow.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d3dfbc819081bd876d95c7c480 |
completed | April 21, 2026, 8:35 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e6190163448190a2404b396215c686 |
completed | April 20, 2026, 12:16 p.m. |
Created at: April 16, 2026, 4:03 p.m.