Triple
T834532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In Evil Hour |
E18040
|
entity |
| Predicate | hasLiteraryStyle |
P6480
|
FINISHED |
| Object | realist narrative |
—
|
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: realist narrative | Statement: [In Evil Hour, hasLiteraryStyle, realist narrative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiteraryStyle Context triple: [In Evil Hour, hasLiteraryStyle, realist narrative]
-
A.
hasLiteraryForm
chosen
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
B.
hasLiterarySignificance
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
-
C.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
D.
literaryInfluence
Indicates that one entity has had a significant impact on the style, themes, or development of another entity’s literary work.
-
E.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abccb94881909cd49aa3fd986b4a |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7c7df881909c539c3ab8ff0367 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.