Triple
T35920625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winter (from the Four Seasons) |
E1038871
|
entity |
| Predicate | hasDepictionOfWeather |
P32056
|
FINISHED |
| Object | winter cold |
—
|
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: winter cold | Statement: [Winter (from the Four Seasons), hasDepictionOfWeather, winter cold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepictionOfWeather Context triple: [Winter (from the Four Seasons), hasDepictionOfWeather, winter cold]
-
A.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
weatherCapability
Indicates that an entity has the ability or functionality to provide, process, or otherwise handle weather-related information or services.
-
C.
hasWeatherContext
Indicates that something is associated with, influenced by, or described in terms of specific weather conditions or patterns.
-
D.
associatedWithWeather
chosen
Indicates a relationship where something is connected or related to weather conditions or phenomena.
-
E.
typicalWeatherFeature
Indicates a weather condition or pattern that commonly characterizes a place or time period.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
Created at: May 3, 2026, 4:07 p.m.