Triple
T31604357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Cascade |
E806436
|
entity |
| Predicate | typicalSeasonalPeak |
P13215
|
FINISHED |
| Object | late winter to 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 winter to spring | Statement: [Golden Cascade, typicalSeasonalPeak, late winter to spring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSeasonalPeak Context triple: [Golden Cascade, typicalSeasonalPeak, late winter to spring]
-
A.
seasonalDemandPeak
Indicates that demand for a product, service, or resource reaches its highest level during a specific recurring season or time period.
-
B.
typicalSeasonTiming
chosen
Indicates the usual time period or season during which something normally occurs or is expected to take place.
-
C.
hasPeakVisitationSeason
Indicates that an entity experiences its highest or most concentrated level of visitation during a specific season or time period.
-
D.
summerPeak
Indicates that something reaches its highest level, intensity, or activity during the summer season.
-
E.
hasSeasonalRidershipPeak
Indicates that the ridership of an entity (such as a service or route) reaches its highest levels during specific seasons or times of the year.
- 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_69f348d54ccc8190a03b5df9a2b40b25 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 10:34 p.m.