Triple
T4724728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith College |
E104854
|
entity |
| Predicate | offersGraduatePrograms |
P21853
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Meredith College, offersGraduatePrograms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersGraduatePrograms Context triple: [Meredith College, offersGraduatePrograms, yes]
-
A.
hasUndergraduatePrograms
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
B.
offersDegree
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
C.
hasDoctoralProgram
Indicates that an institution or academic unit offers and administers a doctoral-level degree program.
-
D.
hasDoctoralPrograms
Indicates that an institution offers one or more doctoral-level academic degree programs.
-
E.
postgraduatePrograms
chosen
Indicates that an institution offers or is associated with academic programs pursued after completion of an undergraduate 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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.