Triple
T37919105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walkerville Elementary School |
E945905
|
entity |
| Predicate | primaryTeacherCharacter |
P176538
|
FINISHED |
| Object | Ms. Frizzle |
E945900
|
NE 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: Ms. Frizzle | Statement: [Walkerville Elementary School, primaryTeacherCharacter, Ms. Frizzle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTeacherCharacter Context triple: [Walkerville Elementary School, primaryTeacherCharacter, Ms. Frizzle]
-
A.
didacticCharacter
Indicates that one entity serves a teaching or instructional role toward another, conveying guidance, lessons, or moral instruction.
-
B.
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.
-
C.
teacherInScene
chosen
Indicates that an entity is acting in the role of a teacher within a particular scene or context.
-
D.
previousTeacher
Indicates that one entity formerly served as a teacher or instructor of the other entity in the past.
-
E.
roleWithTeacher
Indicates a relationship where one entity holds a specific role or position in relation to a teacher.
- F. None of above.
Provenance (4 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4167f617c48190bef93c27bd88ef33 |
completed | June 28, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.