Triple
T5415211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid-Pacific Institute |
E121112
|
entity |
| Predicate | upperGrade |
P63520
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Mid-Pacific Institute, upperGrade, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: upperGrade Context triple: [Mid-Pacific Institute, upperGrade, 12]
-
A.
upperCourseName
Indicates that one course’s name is the uppercase version of another course’s name.
-
B.
highestPass
Indicates that an entity has achieved the greatest passing value, score, or level among a set of compared entities.
-
C.
above
Indicates that one entity is positioned higher than another along a vertical axis, without implying direct contact.
-
D.
admissionsLevel
Indicates the degree or category of access, entry, or acceptance granted in an admissions context.
-
E.
typicalGradeLevel
Indicates the usual or most common educational grade level at which something (such as a concept, resource, or skill) is intended to be taught or is typically encountered.
- 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_69bd463a41cc8190b32ff5af2b96ca93 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87be754c81909c0d0df6216cae46 |
completed | March 20, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8741e8588190863fd5cfb559136d |
completed | March 20, 2026, 5:43 p.m. |
Created at: March 20, 2026, 2:05 p.m.