Triple
T681897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MicroMasters programs |
E13199
|
entity |
| Predicate | relationshipToDegrees |
P10690
|
FINISHED |
| Object | sub-degree credential |
—
|
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: sub-degree credential | Statement: [MicroMasters programs, relationshipToDegrees, sub-degree credential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDegrees Context triple: [MicroMasters programs, relationshipToDegrees, sub-degree credential]
-
A.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
B.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
D.
definesRelationshipBetween
Indicates that one entity specifies or establishes the nature, type, or rules of a relationship that exists between two or more other entities.
-
E.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a06f9ee88190a2d757aacd8e3f5b |
completed | March 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69a49d1f0ccc819088c1527beabcb718 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.