Triple
T4593984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSx Program |
E103563
|
entity |
| Predicate | curriculumType |
P58192
|
FINISHED |
| Object | management curriculum |
—
|
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: management curriculum | Statement: [MSx Program, curriculumType, management curriculum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: curriculumType Context triple: [MSx Program, curriculumType, management curriculum]
-
A.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
B.
usesCurriculum
Indicates that one entity adopts or applies a particular curriculum as the basis for its instruction, training, or educational activities.
-
C.
offersCurriculum
Indicates that one entity provides or makes available a specific curriculum to another entity.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
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.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd593e115081909b11149e02fe4ef3 |
completed | March 20, 2026, 2:27 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:11 p.m.