Triple
T23392216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alypius |
E594048
|
entity |
| Predicate | moralStruggleDescribedIn |
P152083
|
FINISHED |
| Object | Confessions (Augustine) |
—
|
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: Confessions (Augustine) | Statement: [Alypius, moralStruggleDescribedIn, Confessions (Augustine)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralStruggleDescribedIn Context triple: [Alypius, moralStruggleDescribedIn, Confessions (Augustine)]
-
A.
hasMoralConflictAbout
Indicates that an entity experiences internal ethical tension, doubt, or disagreement regarding another entity, action, or situation.
-
B.
moralPortrayal
Indicates how an entity is depicted in terms of moral qualities, such as virtue, vice, or ethical standing, within a given context.
-
C.
moralTheme
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
D.
moralCourage
Indicates the quality of acting ethically or standing up for moral principles despite facing fear, risk, or social pressure.
-
E.
moralTrajectory
Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
- F. None of above. chosen
Provenance (4 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49ca5a0819091b74ca59e7fedd4 |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:36 p.m.