Triple
T32611211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario Secondary School Literacy Test |
E833655
|
entity |
| Predicate | typicalAdministrationYear |
P205116
|
FINISHED |
| Object | second year of secondary school |
—
|
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: second year of secondary school | Statement: [Ontario Secondary School Literacy Test, typicalAdministrationYear, second year of secondary school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAdministrationYear Context triple: [Ontario Secondary School Literacy Test, typicalAdministrationYear, second year of secondary school]
-
A.
planningYear
Indicates the year in which planning or preparation activities for something are scheduled or designated to occur.
-
B.
revenueYear
Indicates the specific year in which the referenced revenue amount is recorded or applies.
-
C.
typicalProjectionYear
Indicates the year that is typically used as the reference point for projecting or forecasting values in a given context.
-
D.
administrativeStateFormationYear
Indicates the year in which an administrative unit or state was formally established or formed.
-
E.
applicationYear
Indicates the year in which an application was submitted or made.
- 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:06 a.m.