Triple
T10886737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justin Ripley |
E257066
|
entity |
| Predicate | hasEthicalAlignment |
P75906
|
FINISHED |
| Object | lawful good |
—
|
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: lawful good | Statement: [Justin Ripley, hasEthicalAlignment, lawful good]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthicalAlignment Context triple: [Justin Ripley, hasEthicalAlignment, lawful good]
-
A.
hasEthicalPosition
chosen
Indicates that an entity holds or is associated with a particular ethical stance, viewpoint, or normative position on moral issues.
-
B.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
-
C.
hasEthicalRole
Indicates that an entity holds a position, function, or responsibility defined in terms of ethical duties, norms, or moral obligations in relation to another entity or context.
-
D.
hasEthicalStandard
Indicates that an entity adheres to, follows, or is governed by a specified set of ethical principles or standards.
-
E.
hasEthicalConstraint
Indicates that an entity is subject to a specified ethical rule, limitation, or normative requirement that governs its behavior or 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751dea1a88190b916879be8d74413 |
completed | April 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69d70d3943c881908895397eccc3e415 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:21 p.m.