Triple
T7774502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electronics and Communication Engineering |
E179157
|
entity |
| Predicate | includesCourse |
P62594
|
FINISHED |
| Object | circuit theory |
—
|
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: circuit theory | Statement: [Electronics and Communication Engineering, includesCourse, circuit theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesCourse Context triple: [Electronics and Communication Engineering, includesCourse, circuit theory]
-
A.
usesCourse
Indicates that one entity makes use of, applies, or relies on a particular course in some context or activity.
-
B.
curriculumIncluded
chosen
Indicates that a particular subject, topic, or component is part of a defined curriculum or course of study.
-
C.
includesInstruction
Indicates that one entity contains, provides, or embeds an instruction or set of instructions directed toward another entity.
-
D.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
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.
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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7046331e0819080ec1a5c23c27cd7 |
completed | March 27, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69c7016f4ce881909c2e9f610255187b |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:11 p.m.