Triple
T33940965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las firmezas de Isabela |
E870162
|
entity |
| Predicate | usesPoeticLanguage |
P182632
|
FINISHED |
| Object | highly metaphorical |
—
|
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: highly metaphorical | Statement: [Las firmezas de Isabela, usesPoeticLanguage, highly metaphorical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPoeticLanguage Context triple: [Las firmezas de Isabela, usesPoeticLanguage, highly metaphorical]
-
A.
usedPoeticallyFor
Indicates that one entity is employed in a poetic or figurative way to refer to or represent another entity.
-
B.
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.
-
C.
poeticStyle
Indicates the stylistic or formal manner in which something is expressed in poetry, such as its structure, tone, and linguistic features.
-
D.
poeticDepiction
chosen
Indicates that one entity artistically represents or describes another using poetic or figurative language.
-
E.
languageOfPoetry
Indicates that a specified language is the language in which a given piece of poetry is written or expressed.
- 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_69f3499b0dd48190b07b4b60babcee02 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 1, 2026, 1:49 a.m.