Triple
T26145869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalton Public Schools |
E659660
|
entity |
| Predicate | providesEducationForGradeLevel |
P3870
|
FINISHED |
| Object | K |
—
|
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: K | Statement: [Dalton Public Schools, providesEducationForGradeLevel, K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesEducationForGradeLevel Context triple: [Dalton Public Schools, providesEducationForGradeLevel, K]
-
A.
servesGradeLevels
chosen
Indicates that an entity (such as a school or program) provides services or instruction to students in the specified grade levels.
-
B.
eligibilityGradeLevel
Indicates the grade level or range of grade levels for which an entity is considered eligible or appropriate.
-
C.
denotesGradeLevel
Indicates that one entity specifies or assigns the educational grade level associated with another entity.
-
D.
eligibleGradeLevels
Indicates the grade levels for which something (such as a program, course, or benefit) is considered eligible or applicable.
-
E.
typicalGradeLevel
Indicates the usual or most common educational grade level at which something (such as a concept, resource, or skill) is intended to be taught or is typically encountered.
- 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_69ee5bc496a88190af7deb7ab5e081de |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 26, 2026, 8:22 p.m.