Triple
T34527437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reverend Paul Ford |
E886436
|
entity |
| Predicate | hasMoralStruggles |
P81120
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Reverend Paul Ford, hasMoralStruggles, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralStruggles Context triple: [Reverend Paul Ford, hasMoralStruggles, true]
-
A.
hasMoralConflictAbout
Indicates that an entity experiences internal ethical tension, doubt, or disagreement regarding another entity, action, or situation.
-
B.
moralStruggleDescribedIn
Indicates that an internal moral conflict or ethical dilemma experienced by an entity is depicted or discussed within a particular work, context, or medium.
-
C.
hasMoralIssue
chosen
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity or situation.
-
D.
hasMoralComplexity
Indicates that the relationship or action involves nuanced ethical considerations, conflicting values, or ambiguity in determining what is morally right or wrong.
-
E.
hasMoralStrategy
Indicates that an entity employs or follows a particular approach or set of principles for making moral or ethical decisions.
- 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_69f349cd7c148190aa99192b126d1527 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
Created at: May 1, 2026, 2:02 a.m.