Triple
T30302321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Seymour |
E770683
|
entity |
| Predicate | typicalWinterSnowfall |
P10513
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Mount Seymour, typicalWinterSnowfall, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWinterSnowfall Context triple: [Mount Seymour, typicalWinterSnowfall, high]
-
A.
averageAnnualSnowfall
chosen
Indicates the typical amount of snow that falls in a given location over the course of a year, averaged across multiple years.
-
B.
snowDepth
Indicates the measured or estimated thickness of accumulated snow at a specific location or time.
-
C.
snowAccumulation
Indicates that snow has collected or built up on a surface or in a location over time.
-
D.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
E.
hasSnowAccumulationRate
Indicates the rate at which snow is accumulating on a surface or in a specified area over time.
- 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_69f224881b948190b8c4921b250a44a3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 7:49 p.m.