Triple
T34649484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Челкаш |
E889793
|
entity |
| Predicate | литературноеНаправлениеСвязь |
P161456
|
FINISHED |
| Object | реализм |
—
|
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: реализм | Statement: [Челкаш, литературноеНаправлениеСвязь, реализм]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: литературноеНаправлениеСвязь Context triple: [Челкаш, литературноеНаправлениеСвязь, реализм]
-
A.
hasLiteraryConnection
Indicates a relationship in which one entity is connected to another through a literary link, such as authorship, reference, influence, adaptation, or shared appearance in written works.
-
B.
literaryCenter
Indicates that a location functions as a primary hub or focal point for literary activity, such as writing, publishing, or literary culture.
-
C.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
D.
usesLiteraryLens
Indicates that one entity analyzes, interprets, or evaluates another entity (such as a text or work) through a specific literary lens or critical framework.
-
E.
literaryGenreAssociated
chosen
Indicates that there is an association between an entity and a particular literary genre with which it is related or classified.
- 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_69f349d825c88190bfc6170ac9281260 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 2:04 a.m.