Triple
T24239593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Utah Asia Campus |
E603183
|
entity |
| Predicate | diplomaType |
P45183
|
FINISHED |
| Object | same diploma as University of Utah main campus |
—
|
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: same diploma as University of Utah main campus | Statement: [University of Utah Asia Campus, diplomaType, same diploma as University of Utah main campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diplomaType Context triple: [University of Utah Asia Campus, diplomaType, same diploma as University of Utah main campus]
-
A.
diplomaText
Indicates that one entity is the textual content or wording that appears on another entity’s diploma.
-
B.
diplomaEquivalence
chosen
Indicates that one diploma or academic qualification is recognized as equivalent in value or status to another.
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
studType
Indicates a relationship where an entity is classified as a particular type or category of stud (e.g., a specific kind of fastener or structural element).
-
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_69e2953f631c819097cbb421046bd417 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28a9eb68c81908a8293c00e581b41 |
completed | April 29, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:03 a.m.