Triple
T8564683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dosa |
E202774
|
entity |
| Predicate | isCourse |
P83664
|
FINISHED |
| Object | main course |
—
|
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: main course | Statement: [Dosa, isCourse, main course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCourse Context triple: [Dosa, isCourse, main course]
-
A.
course
Indicates that an entity is an academic class or unit of instruction offered within an educational program.
-
B.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
C.
isTaughtAs
Indicates that something is presented or delivered as instructional content, typically within an educational or training context.
-
D.
usesCourse
Indicates that one entity makes use of, applies, or relies on a particular course in some context or activity.
-
E.
isLinksCourse
Indicates that one course is linked or associated with another course in a meaningful way (such as being related, connected, or part of the same learning path).
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d11274819099cc33a21a993a1f |
completed | March 31, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30e37ac8190b685df36274602b5 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:20 p.m.