Triple
T7421447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius |
E171254
|
entity |
| Predicate | hasMoralConflictAbout |
P76866
|
FINISHED |
| Object | use of technology for control |
—
|
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: use of technology for control | Statement: [Julius, hasMoralConflictAbout, use of technology for control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralConflictAbout Context triple: [Julius, hasMoralConflictAbout, use of technology for control]
-
A.
hasMoralFraming
Indicates that something is presented or interpreted in terms of moral values, judgments, or ethical considerations.
-
B.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
-
C.
hasMoralPurpose
Indicates that an entity, action, or decision is guided by or oriented toward ethical values, principles, or morally significant goals.
-
D.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
E.
hasMoralCharacteristic
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
- F. None of above. chosen
Provenance (4 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ebc520819087cfc2eb9dda0e17 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1ee5ab8819091082324f2dc3b8c |
completed | March 27, 2026, 9:09 p.m. |
Created at: March 27, 2026, 3:11 p.m.