Triple
T33919685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesca da Rimini, Op. 32 |
E869566
|
entity |
| Predicate | literarySourcePart |
P18697
|
FINISHED |
| Object | Inferno, Canto V |
—
|
NE NERFINISHED |
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: Inferno, Canto V | Statement: [Francesca da Rimini, Op. 32, literarySourcePart, Inferno, Canto V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literarySourcePart Context triple: [Francesca da Rimini, Op. 32, literarySourcePart, Inferno, Canto V]
-
A.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
B.
literaryUnit
chosen
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
-
C.
literaryCenter
Indicates that a location functions as a primary hub or focal point for literary activity, such as writing, publishing, or literary culture.
-
D.
authorialSource
Indicates that one entity serves as the originating author or creator of the content, work, or information associated with another entity.
-
E.
partOfLiteraryProject
Indicates that something is a component or segment belonging to a larger literary project or work.
- 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_69f349992c508190aa4afa24a086cc8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 1, 2026, 1:49 a.m.