Triple
T7247387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oxford Campus |
E156508
|
entity |
| Predicate | typicalYearsOfStudy |
P49391
|
FINISHED |
| Object | first two years of undergraduate study |
—
|
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: first two years of undergraduate study | Statement: [Oxford Campus, typicalYearsOfStudy, first two years of undergraduate study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalYearsOfStudy Context triple: [Oxford Campus, typicalYearsOfStudy, first two years of undergraduate study]
-
A.
primaryDurationOfStudy
chosen
Indicates the main length of time allocated or required for a particular course of study or educational program.
-
B.
typicalAgeAtCompletion
Indicates the age at which an entity (such as a program, activity, or process) is typically completed.
-
C.
majorStudyYear
Indicates the academic year in which an entity (typically a student) is primarily engaged in a particular course of study or major.
-
D.
compulsoryEducationDurationYears
Indicates the number of years that attending school is legally mandatory.
-
E.
matriculationYear
Indicates the calendar year in which an individual formally enrolled or was admitted into an educational program or institution.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea749fb08190841c0aa8c5bd0727 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.