Triple
T11372289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathryn Murphy |
E269370
|
entity |
| Predicate | hasEthicalConcern |
P81120
|
FINISHED |
| Object | victims’ rights |
—
|
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: victims’ rights | Statement: [Kathryn Murphy, hasEthicalConcern, victims’ rights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthicalConcern Context triple: [Kathryn Murphy, hasEthicalConcern, victims’ rights]
-
A.
hasEthicalConstraint
Indicates that an entity is subject to a specified ethical rule, limitation, or normative requirement that governs its behavior or decisions.
-
B.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
-
C.
hasMoralIssue
chosen
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity or situation.
-
D.
hasEthicalPosition
Indicates that an entity holds or is associated with a particular ethical stance, viewpoint, or normative position on moral issues.
-
E.
hasEthicalText
Indicates that an entity is associated with or contains text expressing ethical principles, guidelines, or considerations.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.