Triple
T14874984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WeatherNation TV |
E349843
|
entity |
| Predicate | hasProgrammingCharacteristic |
P89612
|
FINISHED |
| Object | 24-hour weather coverage |
—
|
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: 24-hour weather coverage | Statement: [WeatherNation TV, hasProgrammingCharacteristic, 24-hour weather coverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProgrammingCharacteristic Context triple: [WeatherNation TV, hasProgrammingCharacteristic, 24-hour weather coverage]
-
A.
programmingCharacteristic
chosen
Indicates a relationship where an entity possesses or exhibits a particular property, trait, or quality specifically related to programming.
-
B.
hasProgrammingModel
Indicates that one entity defines, specifies, or is associated with the programming model used or supported by another entity.
-
C.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
D.
hasProgrammingFrom
Indicates that something derives its programming, configuration, or behavioral instructions from a specified source.
-
E.
hasProgrammingTheme
Indicates that something involves, is centered around, or is characterized by programming-related concepts, activities, or content.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e3e5d48190a132f2cf012b01e2 |
completed | April 15, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69de8c1a2bcc81908f914e2e2ced65eb |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:55 a.m.