Triple
T4347987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grossglockner High Alpine Road |
E97950
|
entity |
| Predicate | climateConditions |
P2900
|
FINISHED |
| Object | subject to snow and ice |
—
|
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: subject to snow and ice | Statement: [Grossglockner High Alpine Road, climateConditions, subject to snow and ice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: climateConditions Context triple: [Grossglockner High Alpine Road, climateConditions, subject to snow and ice]
-
A.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
B.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
C.
weatherRole
Indicates a role or function that an entity has in relation to weather conditions or weather-related phenomena.
-
D.
environmentalCondition
chosen
Indicates the state or characteristics of the surrounding physical environment that affect or describe a situation, process, or entity.
-
E.
typicalWeatherNorthernHemisphere
Indicates the characteristic or commonly occurring weather conditions found in the Northern Hemisphere.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351a5559c819081608b0aaf6a0e66 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:15 p.m.