Triple
T13660481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French universities |
E326980
|
entity |
| Predicate | typicalAcademicYearEnd |
P37826
|
FINISHED |
| Object | May or June |
—
|
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: May or June | Statement: [French universities, typicalAcademicYearEnd, May or June]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAcademicYearEnd Context triple: [French universities, typicalAcademicYearEnd, May or June]
-
A.
hasSchoolYearEndMonth
chosen
Indicates the month in which a school year ends for a given educational institution or system.
-
B.
academicYearType
Indicates the classification of an academic year according to its structural or administrative type (e.g., semester-based, quarter-based, fiscal year, etc.).
-
C.
timeWithinAcademicYear
Indicates that a specified time or date falls within the bounds of a defined academic year period.
-
D.
academicTermType
Indicates the category or classification of an academic term within an educational calendar (e.g., semester, quarter, trimester).
-
E.
schoolYear
Indicates the academic year or grade level in which an entity (typically a student or class) is situated within an educational 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc620df208190afaccf3ddd10aa60 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.