Triple
T17983544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Twynam |
E430165
|
entity |
| Predicate | hasSnowSeason |
P82171
|
FINISHED |
| Object | typically June to October |
—
|
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: typically June to October | Statement: [Mount Twynam, hasSnowSeason, typically June to October]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSnowSeason Context triple: [Mount Twynam, hasSnowSeason, typically June to October]
-
A.
hasWinterSportsSeason
Indicates that an entity participates in, is associated with, or has a defined period for winter sports activities or competitions.
-
B.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
C.
hasWinterActivitySeason
Indicates that an entity’s primary period for engaging in a particular activity occurs during the winter season.
-
D.
hasGlacierSkiingSeason
Indicates that a location or ski area offers a skiing season specifically on glacier terrain.
-
E.
hasSeasonalSnowCover
chosen
Indicates that an entity is covered by snow during certain seasons or periods of the year, rather than permanently.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b2992fe481908c0d2757b4de5bad |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.