Triple
T23234391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dum Diversas |
E581245
|
entity |
| Predicate | moralImpact |
P16129
|
FINISHED |
| Object | justification of slavery |
—
|
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: justification of slavery | Statement: [Dum Diversas, moralImpact, justification of slavery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralImpact Context triple: [Dum Diversas, moralImpact, justification of slavery]
-
A.
moralImplication
chosen
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
B.
moralOutcome
Indicates the moral or ethical status resulting from an action, event, or decision, such as whether it is judged right, wrong, good, or bad.
-
C.
moralInfluenceOnCharacter
Indicates that one entity exerts a moral influence that shapes, guides, or alters the character or ethical disposition of another entity.
-
D.
moralTrajectory
Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
-
E.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
- 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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192e7bed88190b914b238c5f49860 |
completed | April 29, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:09 p.m.