Triple
T7273756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stoolbend High School |
E161170
|
entity |
| Predicate | hasFictionalSchoolLevel |
P29320
|
FINISHED |
| Object | secondary education |
—
|
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: secondary education | Statement: [Stoolbend High School, hasFictionalSchoolLevel, secondary education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSchoolLevel Context triple: [Stoolbend High School, hasFictionalSchoolLevel, secondary education]
-
A.
hasFictionalSchool
chosen
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
B.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
C.
publicSchool
Indicates that an educational institution is operated and funded by a government or public authority rather than by private entities.
-
D.
hasSchoolCategory
Indicates that an entity (such as a school or educational institution) is associated with a particular category or type of school.
-
E.
hasSchoolsAccess
Indicates that one entity has permission or the ability to access schools or school-related resources associated with another 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb8a0b4881908ff27c5a75bd4a95 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76a84a081908d4184c55b728e48 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:58 p.m.