Triple
T15885449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monty Brogan |
E385180
|
entity |
| Predicate | hasMoralConflictWith |
P117010
|
FINISHED |
| Object | himself |
—
|
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: himself | Statement: [Monty Brogan, hasMoralConflictWith, himself]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralConflictWith Context triple: [Monty Brogan, hasMoralConflictWith, himself]
-
A.
hasMoralConflictAbout
Indicates that an entity experiences internal ethical tension, doubt, or disagreement regarding another entity, action, or situation.
-
B.
hasMoralIssue
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity or situation.
-
C.
hasEthicalConflictWith
chosen
Indicates a relationship where two entities are in opposition or tension due to differing ethical principles, values, or standards.
-
D.
isMoralFoilFor
Indicates that one entity serves as a contrasting counterpart whose differing moral qualities highlight or emphasize the moral traits of another entity.
-
E.
hasMoralComplexity
Indicates that the relationship or action involves nuanced ethical considerations, conflicting values, or ambiguity in determining what is morally right or wrong.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.