Triple
T5206111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathedral Library, Vercelli |
E117513
|
entity |
| Predicate | hasManuscriptGenre |
P26430
|
FINISHED |
| Object | religious poetry |
—
|
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: religious poetry | Statement: [Cathedral Library, Vercelli, hasManuscriptGenre, religious poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManuscriptGenre Context triple: [Cathedral Library, Vercelli, hasManuscriptGenre, religious poetry]
-
A.
manuscriptType
Indicates the specific category or kind of manuscript associated with an entity (e.g., draft, final version, annotated copy).
-
B.
hasWrittenWorkType
chosen
Indicates that an entity (typically a written work) is associated with a specific type or category of written work (such as novel, article, report, etc.).
-
C.
publishedGenre
Indicates that an entity has been published in, or is associated with, a particular genre.
-
D.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
E.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a490338819080481df79d3aae01 |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.