Triple
T34586041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Maudie Atkinson |
E888045
|
entity |
| Predicate | attitudeTowardChildren |
P166245
|
FINISHED |
| Object | treats children with respect |
—
|
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: treats children with respect | Statement: [Miss Maudie Atkinson, attitudeTowardChildren, treats children with respect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attitudeTowardChildren Context triple: [Miss Maudie Atkinson, attitudeTowardChildren, treats children with respect]
-
A.
attitudeTowardDependents
chosen
Indicates the nature or quality of an entity’s feelings, stance, or behavior toward those who depend on it.
-
B.
attitudeTowardFamily
Indicates a person’s feelings, beliefs, or stance regarding their family as a whole or specific family members.
-
C.
attitudeTowardEducation
Indicates an entity’s feelings, beliefs, or stance regarding education or educational practices.
-
D.
attitudeTowardOthers
Indicates the nature or disposition of one entity’s feelings, judgments, or behavioral stance toward other entities.
-
E.
attitudeTowardFilialPiety
Indicates an entity’s stance, evaluation, or feelings regarding the value, practice, or importance of filial piety.
- 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.