Triple
T15714160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let Us Have Peace |
E380915
|
entity |
| Predicate | hasMoralAppeal |
P57332
|
FINISHED |
| Object | forgiveness |
—
|
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: forgiveness | Statement: [Let Us Have Peace, hasMoralAppeal, forgiveness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralAppeal Context triple: [Let Us Have Peace, hasMoralAppeal, forgiveness]
-
A.
hasMoralAudience
Indicates that an action, statement, or agent is directed toward or evaluated by a group that can judge it in moral or ethical terms.
-
B.
hasMoralFraming
Indicates that something is presented or interpreted in terms of moral values, judgments, or ethical considerations.
-
C.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
-
D.
hasMoralMessage
chosen
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
-
E.
hasMoralIssue
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f90aea0819082a9e9fe0f7780b0 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.