Triple
T2442125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rainbow Falls (Mammoth Lakes) |
E53299
|
entity |
| Predicate | winterAccess |
P10789
|
FINISHED |
| Object | often limited by snow |
—
|
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: often limited by snow | Statement: [Rainbow Falls (Mammoth Lakes), winterAccess, often limited by snow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterAccess Context triple: [Rainbow Falls (Mammoth Lakes), winterAccess, often limited by snow]
-
A.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
B.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
-
C.
requiresEquipmentInWinter
Indicates that performing the related activity or fulfilling the related condition necessitates the use of specific equipment during winter.
-
D.
summerWinterCycle
Indicates a recurring transition between summer and winter seasons, capturing the cyclical change in conditions or states across these two periods.
-
E.
winterAscentFirstDate
Indicates the calendar date on which the first successful winter ascent of something (such as a route, peak, or wall) took place.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcabf477081908512df63ac1a6414 |
completed | March 7, 2026, 6:50 a.m. |
| PD | Predicate disambiguation | batch_69abc5ad8e588190b97c4cd7cf575043 |
completed | March 7, 2026, 6:29 a.m. |
Created at: March 6, 2026, 9:43 p.m.