Triple
T17922842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSc in Management |
E448114
|
entity |
| Predicate | commonCourses |
P11940
|
FINISHED |
| Object | organizational behavior |
—
|
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: organizational behavior | Statement: [MSc in Management, commonCourses, organizational behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonCourses Context triple: [MSc in Management, commonCourses, organizational behavior]
-
A.
typicalCourse
chosen
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.
courseCup
Indicates that a particular cup is used for or associated with serving a specific course in a meal.
-
C.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
D.
commonlyTaughtWith
Indicates that two subjects or concepts are frequently taught together within the same course, lesson, or curriculum context.
-
E.
notableCourseType
Indicates that a course has a particular notable or distinguished type or classification (e.g., flagship, honors, or otherwise specially recognized).
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30ad8748190b28d3e8b5afab2ef |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:20 a.m.