Triple
T37140593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Context. Diana Vishneva Festival |
E920094
|
entity |
| Predicate | languageOfArt |
P203375
|
FINISHED |
| Object | non-verbal performance |
—
|
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: non-verbal performance | Statement: [Context. Diana Vishneva Festival, languageOfArt, non-verbal performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfArt Context triple: [Context. Diana Vishneva Festival, languageOfArt, non-verbal performance]
-
A.
languageUsedInDepiction
Indicates that a particular language is used within a depiction, such as in its text, dialogue, or other linguistic content.
-
B.
artSpecialty
Indicates that an entity’s primary focus, expertise, or specialization is in a particular art form or artistic domain.
-
C.
artwork
Indicates that one entity is an artwork created, presented, or associated with another entity (such as an artist, collection, or institution).
-
D.
artisticField
Indicates the artistic domain or creative discipline in which an entity is active or associated.
-
E.
artworkType
Indicates the specific category or kind of artwork that characterizes the relationship between the subject and the artwork.
- 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_69f76e9e9d008190a250b0387c992c74 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a016ebba0448190b5319243e1b2feca |
completed | May 11, 2026, 5:52 a.m. |
| PD | Predicate disambiguation | batch_6a016d2486b4819085efe197ee21b707 |
completed | May 11, 2026, 5:46 a.m. |
| PDg | Predicate description generation | batch_6a016ebace208190af9a6d6d8a31c670 |
completed | May 11, 2026, 5:52 a.m. |
Created at: May 3, 2026, 4:15 p.m.