Triple
T8076699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Houses of Parliament, Effect of Sun in the Fog |
E188508
|
entity |
| Predicate | depictionOfWeather |
P1702
|
FINISHED |
| Object | foggy conditions |
—
|
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: foggy conditions | Statement: [The Houses of Parliament, Effect of Sun in the Fog, depictionOfWeather, foggy conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictionOfWeather Context triple: [The Houses of Parliament, Effect of Sun in the Fog, depictionOfWeather, foggy conditions]
-
A.
weatherRole
Indicates a role or function that an entity has in relation to weather conditions or weather-related phenomena.
-
B.
weatherCondition
chosen
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
C.
depictsMood
Indicates that one entity visually represents or conveys the emotional state or mood of another entity.
-
D.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
E.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
- 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a184488190b19ef7066f0f5057 |
completed | March 31, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:28 p.m.