Triple
T38398504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of Data Science |
E900829
|
entity |
| Predicate | commonPrerequisiteBackground |
P137575
|
FINISHED |
| Object | computer science |
—
|
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: computer science | Statement: [Master of Data Science, commonPrerequisiteBackground, computer science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonPrerequisiteBackground Context triple: [Master of Data Science, commonPrerequisiteBackground, computer science]
-
A.
commonPrerequisiteField
chosen
Indicates that two or more items share the same required prerequisite field that must be satisfied before they can proceed or be accessed.
-
B.
prerequisiteKnowledge
Indicates that one piece of knowledge must be acquired or understood before another can be effectively learned or applied.
-
C.
typicalBackground
Indicates that an entity has a usual or commonly expected background, context, or setting associated with it.
-
D.
socialBackground
Indicates a relationship where one entity’s social origin, class, or upbringing context is associated with or characterizes another entity.
-
E.
typicalStudentBackground
Indicates that an entity has the usual or commonly expected background or profile for a student in a given context.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff7ae5d088819089aa3b6360b6b749 |
completed | May 9, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69ff7a4df6488190bf60d675b36b1d6d |
completed | May 9, 2026, 6:17 p.m. |
Created at: May 3, 2026, 4:31 p.m.