Triple
T7273757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stoolbend High School |
E161170
|
entity |
| Predicate | hasFictionalSchoolType |
P19184
|
FINISHED |
| Object | public high 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: public high school | Statement: [Stoolbend High School, hasFictionalSchoolType, public high school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSchoolType Context triple: [Stoolbend High School, hasFictionalSchoolType, public high school]
-
A.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
B.
hasSchoolCategory
chosen
Indicates that an entity (such as a school or educational institution) is associated with a particular category or type of school.
-
C.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
D.
publicSchool
Indicates that an educational institution is operated and funded by a government or public authority rather than by private entities.
-
E.
setInFictionalUniversity
Indicates that the events or narrative take place within the setting of a fictional university.
- 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.