Triple
T7421456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius |
E171254
|
entity |
| Predicate | hasLiteraryTheme |
P61759
|
FINISHED |
| Object | resistance to change |
—
|
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: resistance to change | Statement: [Julius, hasLiteraryTheme, resistance to change]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiteraryTheme Context triple: [Julius, hasLiteraryTheme, resistance to change]
-
A.
literaryThemeInvolvement
chosen
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
-
B.
hasLiterarySignificance
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
-
C.
hasLiteraryContext
Indicates that something is associated with, situated within, or explained by a particular literary context (such as a work, genre, period, or interpretive framework).
-
D.
hasLiteraryForm
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
E.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ebc520819087cfc2eb9dda0e17 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.