Triple
T16693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everett Public Schools |
E332
|
entity |
| Predicate | hasSchoolLevel |
P177
|
FINISHED |
| Object | elementary school |
—
|
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: elementary school | Statement: [Everett Public Schools, hasSchoolLevel, elementary school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSchoolLevel Context triple: [Everett Public Schools, hasSchoolLevel, elementary school]
-
A.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
B.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
C.
educationType
chosen
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
E.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fec1fe8819080da6f2c745dc8fd |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.