Triple
T712590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YouTube Shorts |
E14241
|
entity |
| Predicate | contentDiscoveryMechanism |
P7311
|
FINISHED |
| Object | algorithmic recommendation |
—
|
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: algorithmic recommendation | Statement: [YouTube Shorts, contentDiscoveryMechanism, algorithmic recommendation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentDiscoveryMechanism Context triple: [YouTube Shorts, contentDiscoveryMechanism, algorithmic recommendation]
-
A.
discoveryMethod
chosen
Indicates the process, technique, or approach by which something was found, detected, or identified.
-
B.
contentProvider
Indicates that one entity serves as the source or supplier of content (such as media, information, or data) for another entity.
-
C.
primaryContent
Indicates that one entity serves as the main or most important content associated with another entity.
-
D.
popularFor
Indicates that something is widely liked, recognized, or favored specifically because of a particular feature, quality, or use.
-
E.
mediaOrigin
Indicates the original source or provenance from which a piece of media (such as an image, video, or audio) was derived or obtained.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f221b081909fbaa689fb20eb3e |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.