Triple
T285896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver Rule |
E5883
|
entity |
| Predicate | ethicalFocus |
P3363
|
FINISHED |
| Object | avoidance of harm |
—
|
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: avoidance of harm | Statement: [Silver Rule, ethicalFocus, avoidance of harm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethicalFocus Context triple: [Silver Rule, ethicalFocus, avoidance of harm]
-
A.
ethicalDebate
Indicates a relationship where parties are engaged in discussing, questioning, or disputing the moral rightness or wrongness of actions, policies, or principles.
-
B.
positionOnEthics
Indicates a stance, viewpoint, or opinion that an entity holds regarding ethical principles, issues, or practices.
-
C.
ethos
chosen
Indicates the characteristic spirit, values, or guiding beliefs that define how an individual, group, or organization thinks and behaves.
-
D.
hasEthicalAssessment
Indicates that an entity has been evaluated according to ethical criteria or standards.
-
E.
virtue
Indicates that an entity possesses or exemplifies a morally good quality, trait, or behavior.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a2605b372c8190831570aa6532cc96 |
completed | Feb. 28, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69a25b7a8d148190aacdcc8ccb35c7f3 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.