Triple
T11205376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of Science in Computational Analysis and Public Policy |
E265146
|
entity |
| Predicate | academic degree program |
P2489
|
FINISHED |
| Object | master’s program |
—
|
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’s program | Statement: [Master of Science in Computational Analysis and Public Policy, academic degree program, master’s program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academic degree program Context triple: [Master of Science in Computational Analysis and Public Policy, academic degree program, master’s program]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
C.
academicProgramsMedium
Indicates the medium or format through which academic programs are delivered (e.g., online, in-person, hybrid).
-
D.
hasAcademicProgramsWith
Indicates that two institutions or entities offer or participate in the same or jointly organized academic programs.
-
E.
hasEducationalProgram
chosen
Indicates that an entity offers, runs, or is associated with a specific educational program.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d4eef88190a7f05bca82d919b9 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:30 p.m.