Triple
T24263964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judy Moody and the Not Bummer Summer |
E604787
|
entity |
| Predicate | leadCharacterSchoolGrade |
P68816
|
FINISHED |
| Object | third grade |
—
|
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: third grade | Statement: [Judy Moody and the Not Bummer Summer, leadCharacterSchoolGrade, third grade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterSchoolGrade Context triple: [Judy Moody and the Not Bummer Summer, leadCharacterSchoolGrade, third grade]
-
A.
studentCharacter
Indicates that one entity has the role or qualities of a student in relation to another entity, typically within an educational or learning context.
-
B.
schoolRole
Indicates the specific function, position, or capacity an entity holds within a school context (e.g., student, teacher, administrator).
-
C.
schoolChampionFor
Indicates that one entity serves as a leading advocate, representative, or top performer for a particular school.
-
D.
denotesGradeLevel
Indicates that one entity specifies or assigns the educational grade level associated with another entity.
-
E.
gradeName
chosen
Indicates the specific name or label assigned to a grade level associated with an entity.
- 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_69e29544c29c8190b023606eafe5d36a |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28c6a4cc88190914f1c52567d613a |
completed | April 29, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:06 a.m.