Triple
T5094691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old English homilies |
E114837
|
entity |
| Predicate | rhetoricalFeatures |
P16928
|
FINISHED |
| Object | repetition |
—
|
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: repetition | Statement: [Old English homilies, rhetoricalFeatures, repetition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rhetoricalFeatures Context triple: [Old English homilies, rhetoricalFeatures, repetition]
-
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.
rhetoricalStyle
Indicates the characteristic manner or technique of expression used in communication, such as tone, structure, and persuasive strategies.
-
C.
literaryFeature
chosen
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
E.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7563ad608190879a26a0bf07c3f6 |
completed | March 20, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:40 p.m.