Triple
T9111397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potiphar's wife |
E218607
|
entity |
| Predicate | associatedWithVirtueByContrast |
P48459
|
FINISHED |
| Object | Joseph's chastity |
—
|
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: Joseph's chastity | Statement: [Potiphar's wife, associatedWithVirtueByContrast, Joseph's chastity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithVirtueByContrast Context triple: [Potiphar's wife, associatedWithVirtueByContrast, Joseph's chastity]
-
A.
vowedVirtue
Indicates that an entity has formally promised or committed to uphold a particular virtue or moral quality.
-
B.
moralAssociation
chosen
Indicates a perceived ethical or moral connection between entities, such as one influencing or reflecting the moral character, values, or judgment of the other.
-
C.
virtue
Indicates that an entity possesses or exemplifies a morally good quality, trait, or behavior.
-
D.
viewsAsVirtue
Indicates that one entity regards a particular trait, behavior, or quality as a moral virtue.
-
E.
virtueIllustrated
Indicates that an action, example, or situation serves to demonstrate or make clear a particular virtue.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8495c448190b9bb3803fb2dda70 |
completed | April 1, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69cc65fe5be081909d4470d6317b14a6 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:16 p.m.