Triple
T28711349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APT |
E729838
|
entity |
| Predicate | channelContent |
P165547
|
FINISHED |
| Object | visible light imagery |
—
|
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: visible light imagery | Statement: [APT, channelContent, visible light imagery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: channelContent Context triple: [APT, channelContent, visible light imagery]
-
A.
channels
Indicates that one entity serves as a medium, route, or conduit through which another entity is directed, transmitted, or delivered.
-
B.
channelCategory
Indicates that a channel belongs to or is classified under a particular category.
-
C.
channelName
Indicates the specific name assigned to a communication channel through which content, messages, or data are transmitted or organized.
-
D.
YouTubeChannelTopic
Indicates that a YouTube channel is primarily about or associated with a particular topic or subject area.
-
E.
channelSpecialization
Indicates that one channel is a more specialized or focused version of another, typically refining or narrowing the scope of the broader channel.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6596b210481908af6cd555748f75b |
completed | May 2, 2026, 8:07 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f658ebeca4819096beb3f98f73fe31 |
completed | May 2, 2026, 8:05 p.m. |
Created at: April 28, 2026, 5:48 a.m.