Triple
T29377253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bronson Junior/Senior High School |
E745033
|
entity |
| Predicate | combinedSchool |
P166693
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bronson Junior/Senior High School, combinedSchool, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combinedSchool Context triple: [Bronson Junior/Senior High School, combinedSchool, yes]
-
A.
partnerSchool
Indicates a formal collaborative relationship between two educational institutions, typically involving shared programs, resources, or exchange activities.
-
B.
alsoAttendedSchool
Indicates that two or more entities attended the same school in addition to any other schools they may have attended.
-
C.
publicSchool
Indicates that an educational institution is operated and funded by a government or public authority rather than by private entities.
-
D.
schoolAttended
Indicates that one entity has attended, or been enrolled as a student at, the school represented by the other entity.
-
E.
schoolOf
Indicates that an educational institution is the one where a person studied, worked, or is otherwise academically affiliated.
- F. None of above. chosen
Provenance (4 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669aeb2208190b5b578c5d94edb63 |
completed | May 2, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661b47d088190934f63884a203261 |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 28, 2026, 2:32 p.m.