Triple
T26439957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hornsby Girls' High School |
E665059
|
entity |
| Predicate | maximumYearLevel |
P105749
|
FINISHED |
| Object | Year 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: Year 12 | Statement: [Hornsby Girls' High School, maximumYearLevel, Year 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumYearLevel Context triple: [Hornsby Girls' High School, maximumYearLevel, Year 12]
-
A.
upperLevelCompletionYear
Indicates the year in which an entity completed an upper-level stage of education, training, or qualification.
-
B.
gradeRangeEnd
chosen
Indicates the upper boundary or final value in a specified grade range for an entity.
-
C.
upperGrade
Indicates that one entity is in a higher grade level than another entity.
-
D.
majorStudyYear
Indicates the academic year in which an entity (typically a student) is primarily engaged in a particular course of study or major.
-
E.
eligibleGradeLevels
Indicates the grade levels for which something (such as a program, course, or benefit) is considered eligible or applicable.
- 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_69ee883c851881909e2ab04efbb3c5fe |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 26, 2026, 11:57 p.m.