Triple
T14636406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor Bellingham |
E343617
|
entity |
| Predicate | treatsAsMoralIssue |
P63895
|
FINISHED |
| Object | Hester Prynne’s adultery |
—
|
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: Hester Prynne’s adultery | Statement: [Governor Bellingham, treatsAsMoralIssue, Hester Prynne’s adultery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsAsMoralIssue Context triple: [Governor Bellingham, treatsAsMoralIssue, Hester Prynne’s adultery]
-
A.
hasMoralIssue
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity or situation.
-
B.
hasMoralConflictAbout
Indicates that an entity experiences internal ethical tension, doubt, or disagreement regarding another entity, action, or situation.
-
C.
hasMoralFraming
chosen
Indicates that something is presented or interpreted in terms of moral values, judgments, or ethical considerations.
-
D.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
E.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ab9578819085b4cf7244d30d87 |
completed | April 14, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.