Triple
T1870283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin High School (Somerset County, New Jersey) |
E39018
|
entity |
| Predicate | gradesServed |
P3870
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Franklin High School (Somerset County, New Jersey), gradesServed, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gradesServed Context triple: [Franklin High School (Somerset County, New Jersey), gradesServed, 9]
-
A.
servesGradeLevels
chosen
Indicates that an entity (such as a school or program) provides services or instruction to students in the specified grade levels.
-
B.
grades
Indicates that one entity evaluates and assigns a score or level of performance to another entity.
-
C.
gradeCount
Indicates the number of grades associated with a given entity or context.
-
D.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
-
E.
gradeNumber
Indicates the numerical grade or level assigned to an entity within an ordered grading or classification system.
- 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0f79fbc819085c54f3189a552d9 |
completed | March 7, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69abafe2b56c81909e13d543982e6e13 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.