Triple
T2813259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Electrical and Computer Engineering |
E54221
|
entity |
| Predicate | typicalCourseTopic |
P43765
|
FINISHED |
| Object | circuits |
—
|
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: circuits | Statement: [Department of Electrical and Computer Engineering, typicalCourseTopic, circuits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCourseTopic Context triple: [Department of Electrical and Computer Engineering, typicalCourseTopic, circuits]
-
A.
typicalCourse
Indicates that one entity is a standard or commonly taken course associated with another entity, such as a program, curriculum, or field of study.
-
B.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
C.
courseName
Indicates the specific name or title assigned to a course in an educational context.
-
D.
commonlyTaughtWith
Indicates that two subjects or concepts are frequently taught together within the same course, lesson, or curriculum context.
-
E.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4a31d081909377044d5ff791b0 |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde0f4c648190b9812e64f30c39da |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 9:59 p.m.