Triple
T15740691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A View of the Woods |
E381592
|
entity |
| Predicate | hasMoralOrReligiousDimension |
P18695
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [A View of the Woods, hasMoralOrReligiousDimension, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralOrReligiousDimension Context triple: [A View of the Woods, hasMoralOrReligiousDimension, true]
-
A.
hasEthicalDimension
chosen
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
-
B.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
-
C.
hasMoralFraming
Indicates that something is presented or interpreted in terms of moral values, judgments, or ethical considerations.
-
D.
hasMoralIssue
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity or situation.
-
E.
moralBelief
Indicates that an agent holds a normative judgment about what is right, wrong, good, or bad in a given context.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.