Triple
T29681101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CCTV Spring Festival Gala |
E750952
|
entity |
| Predicate | viewershipScale |
P37957
|
FINISHED |
| Object | hundreds of millions of viewers |
—
|
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: hundreds of millions of viewers | Statement: [CCTV Spring Festival Gala, viewershipScale, hundreds of millions of viewers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewershipScale Context triple: [CCTV Spring Festival Gala, viewershipScale, hundreds of millions of viewers]
-
A.
viewershipImpact
Indicates how one entity’s viewership levels influence or change the audience size, engagement, or visibility of another entity.
-
B.
viewershipNote
Indicates a note or annotation providing additional information or context about the viewership of something.
-
C.
viewershipEstimateUnit
Indicates the unit of measurement used to express a viewership estimate (e.g., viewers, households, percentage).
-
D.
audienceScale
chosen
Indicates the relative size or reach of the audience associated with an entity, event, or communication.
-
E.
USViewers
Indicates the number or set of viewers located in the United States who watched or were exposed to a particular piece of content or event.
- 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_69f0d624d7b08190ba237d226f78d0d9 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67261a8f081908e1eca98a9b1ae23 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:10 p.m.