Triple
T26285744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voksenkollen station |
E661131
|
entity |
| Predicate | hasSnowRelatedTrafficPeaks |
P160557
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Voksenkollen station, hasSnowRelatedTrafficPeaks, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSnowRelatedTrafficPeaks Context triple: [Voksenkollen station, hasSnowRelatedTrafficPeaks, yes]
-
A.
hasSnowAndIce
Indicates that the subject is covered with or contains both snow and ice.
-
B.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
C.
hasSnowRisk
Indicates that there is a potential or likelihood of snow affecting the related entity or situation.
-
D.
hasHeavySnowfall
Indicates that a location or area is experiencing or characterized by a large amount of snowfall.
-
E.
hasSnowOccasionally
Indicates that the subject experiences snowfall at irregular or infrequent intervals rather than regularly or never.
- 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_69ee812bbd448190be4d7478b057990a |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60e77611081908d8719871d42015a |
completed | May 2, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f6037bf7a081908862a8359be80cf8 |
completed | May 2, 2026, 2 p.m. |
Created at: April 26, 2026, 10:04 p.m.