Triple
T25833680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olney Elementary School |
E650732
|
entity |
| Predicate | usesSchoolLevel |
P165319
|
FINISHED |
| Object | elementary school level |
—
|
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 level | Statement: [Olney Elementary School, usesSchoolLevel, elementary school level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSchoolLevel Context triple: [Olney Elementary School, usesSchoolLevel, elementary school level]
-
A.
isSchoolFor
Indicates that one entity functions as an educational institution intended to serve, teach, or train the other entity.
-
B.
hasSchoolSystemLevel
chosen
Indicates that an educational institution is associated with a particular level or tier within a school system (e.g., primary, secondary, tertiary).
-
C.
operatesOnSchoolLevel
Indicates that an entity performs actions or has responsibilities at the level of a school as an organizational unit.
-
D.
eligibleGradeLevels
Indicates the grade levels for which something (such as a program, course, or benefit) is considered eligible or applicable.
-
E.
hasUpperSchool
Indicates that an educational institution includes or is associated with an upper-level school (typically serving older or advanced 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 22, 2026, 7:39 a.m.