Triple
T28510586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Poetic Principle |
E721471
|
entity |
| Predicate | proposesViewOfPoetryAs |
P77792
|
FINISHED |
| Object | art devoted to beauty |
—
|
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: art devoted to beauty | Statement: [The Poetic Principle, proposesViewOfPoetryAs, art devoted to beauty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proposesViewOfPoetryAs Context triple: [The Poetic Principle, proposesViewOfPoetryAs, art devoted to beauty]
-
A.
viewsPoetryAs
chosen
Indicates that one entity regards or interprets poetry in a particular way or from a specific perspective.
-
B.
poeticCategory
Indicates that one entity is classified as belonging to a particular poetic category or type of poetry in relation to another entity.
-
C.
poeticParaphrasedIn
Indicates that one expression is rendered as a poetic or stylistically embellished paraphrase of another expression.
-
D.
exemplifiedByPoet
Indicates that something is characteristically or ideally represented by a particular poet.
-
E.
usesPoeticProgram
Indicates that one entity employs or applies a poetic program—such as a structured, rule-based, or stylistically poetic system—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_69f01a5c072081908c7b04bcf6478da9 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 28, 2026, 3:12 a.m.