Triple
T22045157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igor Severyanin |
E544740
|
entity |
| Predicate | usedLiteraryDevice |
P16928
|
FINISHED |
| Object | neologisms |
—
|
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: neologisms | Statement: [Igor Severyanin, usedLiteraryDevice, neologisms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLiteraryDevice Context triple: [Igor Severyanin, usedLiteraryDevice, neologisms]
-
A.
rhetoricalDevice
Indicates that one entity is used as a rhetorical device in relation to another, such as a figure of speech, stylistic technique, or persuasive strategy within a discourse.
-
B.
literaryUse
Indicates that something is employed or referenced within a literary context, such as in a written work, style, or technique.
-
C.
lyricalDevice
Indicates the use of a specific poetic or musical technique within lyrics to achieve a particular expressive or aesthetic effect.
-
D.
literaryFeature
chosen
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
E.
hasPoeticDevice
Indicates that one entity (typically a text or passage) employs or contains a specific poetic device present in the other entity.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1282e647481908e054b3ad19e2c15 |
completed | April 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:25 p.m.