Triple
T3988938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brother Justin Crowe |
E86939
|
entity |
| Predicate | moralCharacteristic |
P47751
|
FINISHED |
| Object | corrupt |
—
|
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: corrupt | Statement: [Brother Justin Crowe, moralCharacteristic, corrupt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralCharacteristic Context triple: [Brother Justin Crowe, moralCharacteristic, corrupt]
-
A.
hasMoralCharacteristic
chosen
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
B.
virtue
Indicates that an entity possesses or exemplifies a morally good quality, trait, or behavior.
-
C.
moralTheme
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
D.
moralAssociation
Indicates a perceived ethical or moral connection between entities, such as one influencing or reflecting the moral character, values, or judgment of the other.
-
E.
moralExemplarOf
Indicates that one entity serves as a model or standard of moral behavior for another entity or group.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.