Triple
T8018988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MS in Information Systems |
E186690
|
entity |
| Predicate | typicalDegreeTitle |
P48121
|
FINISHED |
| Object | Master of Science in Information Systems |
—
|
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: Master of Science in Information Systems | Statement: [MS in Information Systems, typicalDegreeTitle, Master of Science in Information Systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDegreeTitle Context triple: [MS in Information Systems, typicalDegreeTitle, Master of Science in Information Systems]
-
A.
typicalDegreeName
chosen
Indicates the standard or commonly used academic degree title associated with an educational program or qualification.
-
B.
typicalDegreeLevels
Indicates the usual or commonly expected academic degree levels associated with a given entity or context.
-
C.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
D.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
E.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df626e8819098a9f8908dfdad3b |
completed | March 31, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69cb049253d08190bafcecfde493ab8b |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:20 p.m.