Triple
T6372361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NASCAR Technical Institute |
E143379
|
entity |
| Predicate | hasTargetStudent |
P11007
|
FINISHED |
| Object | high school graduates |
—
|
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: high school graduates | Statement: [NASCAR Technical Institute, hasTargetStudent, high school graduates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetStudent Context triple: [NASCAR Technical Institute, hasTargetStudent, high school graduates]
-
A.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
B.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
C.
hasStudentCategory
Indicates that an entity is classified under a specific category or type of student.
-
D.
targetStudentGroup
chosen
Indicates a relationship where something is directed, tailored, or intended specifically for a particular group of students.
-
E.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06829d76c819092b476631459233a |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.