Triple
T37725636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book II (Zanoni) |
E939709
|
entity |
| Predicate | isSectionOfNovelWithTheme |
P61759
|
FINISHED |
| Object | mysticism |
—
|
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: mysticism | Statement: [Book II (Zanoni), isSectionOfNovelWithTheme, mysticism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSectionOfNovelWithTheme Context triple: [Book II (Zanoni), isSectionOfNovelWithTheme, mysticism]
-
A.
isSectionOfComicNovel
Indicates that one entity is a section or part of a comic novel.
-
B.
basedInNovel
Indicates that something (such as a work, adaptation, or element) is derived from, set in, or primarily grounded in the narrative world of a particular novel.
-
C.
hasNovella
Indicates that one entity possesses, includes, or is associated with a novella as part of its contents or attributes.
-
D.
worksForInNovel
Indicates that one entity is employed by or serves another entity within the fictional context of a specific novel.
-
E.
literaryThemeInvolvement
chosen
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef0cec881908c2742d77d145901 |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.