Triple
T575564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YouTube Stories |
E13753
|
entity |
| Predicate | interaction |
P3970
|
FINISHED |
| Object | view counts |
—
|
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: view counts | Statement: [YouTube Stories, interaction, view counts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interaction Context triple: [YouTube Stories, interaction, view counts]
-
A.
interactionPoint
Indicates a specific location or moment where two or more entities come into contact or engage with each other.
-
B.
participation
Indicates that an entity takes part in, contributes to, or is involved in a shared activity, event, or process with others.
-
C.
hasInteraction
chosen
Indicates that there is some form of interaction or mutual action occurring between the related entities.
-
D.
context
Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
-
E.
usesIntervention
Indicates that one entity applies, employs, or relies on a specific intervention (such as a treatment, method, or strategy) in relation to another entity or context.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b67395c8190a8046ff7debe9d1f |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.