Triple
T27664759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YouTube Data API |
E697201
|
entity |
| Predicate | exposesResource |
P54169
|
FINISHED |
| Object | video |
—
|
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: video | Statement: [YouTube Data API, exposesResource, video]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exposesResource Context triple: [YouTube Data API, exposesResource, video]
-
A.
exposesTo
Indicates that one entity subjects another entity to contact with or influence from something, typically involving risk, effect, or experience.
-
B.
exposes
Indicates making something visible, known, or vulnerable by removing cover, concealment, or protection.
-
C.
exposedAs
Indicates that one entity reveals or publicly identifies another entity as having a hidden, false, or previously concealed role, identity, or nature.
-
D.
exposedThrough
Indicates that something becomes revealed, accessible, or affected as a result of passing through or being subjected to another thing or medium.
-
E.
providesExposureTo
chosen
Indicates that one entity gives another entity the opportunity to be seen, noticed, or become known by a particular audience, environment, or set of influences.
- 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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 2:37 p.m.