Triple
T34586014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Maudie Atkinson |
E888045
|
entity |
| Predicate | moralRoleModelFor |
P44622
|
FINISHED |
| Object | Scout Finch |
—
|
NE NERFINISHED |
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: Scout Finch | Statement: [Miss Maudie Atkinson, moralRoleModelFor, Scout Finch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralRoleModelFor Context triple: [Miss Maudie Atkinson, moralRoleModelFor, Scout Finch]
-
A.
moralExemplarOf
chosen
Indicates that one entity serves as a model or standard of moral behavior for another entity or group.
-
B.
literaryRoleModelFor
Indicates that one entity serves as an inspirational or exemplary figure in a literary context for another entity.
-
C.
moralNarrativeRole
Indicates the role an entity plays within a moral storyline or ethical framing, such as being portrayed as virtuous, villainous, victimized, or morally ambiguous.
-
D.
moralInfluenceOnCharacter
Indicates that one entity exerts a moral influence that shapes, guides, or alters the character or ethical disposition of another entity.
-
E.
moralTrajectory
Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
- 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_69f349d25cbc8190869998de5915886b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f720c7ea608190bd92d69643330823 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:03 a.m.