Triple
T29471966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Служебный роман |
E747531
|
entity |
| Predicate | музыкальная тема |
P7259
|
FINISHED |
| Object | песня «У природы нет плохой погоды» |
—
|
NE NERFINISHED |
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: песня «У природы нет плохой погоды» | Statement: [Служебный роман, музыкальная тема, песня «У природы нет плохой погоды»]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: музыкальная тема Context triple: [Служебный роман, музыкальная тема, песня «У природы нет плохой погоды»]
-
A.
musicThemeType
Indicates the specific category or type of musical theme associated with a piece, segment, or motif.
-
B.
cinematicTheme
Indicates that something embodies, expresses, or is characterized by a particular theme commonly used in cinema or film narratives.
-
C.
themeMusicFor
Indicates that one entity serves as the theme music or signature tune specifically composed or selected for another entity, such as a show, character, or event.
-
D.
albumTheme
Indicates that one entity is the central subject, concept, or motif that thematically unifies the other entity, which is an album.
-
E.
hasThemeSong
chosen
Indicates that an entity is associated with or characterized by a particular theme song.
- 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_69f0bd42cf308190bb01b20bc5b7c2d0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66babf5e08190b8e1007546f3881a |
completed | May 2, 2026, 9:25 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:58 p.m.