Triple
T97187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Triangle (universities) |
E1957
|
entity |
| Predicate | involvesTypeOfInstitution |
P303
|
FINISHED |
| Object | public research university |
—
|
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: public research university | Statement: [Golden Triangle (universities), involvesTypeOfInstitution, public research university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesTypeOfInstitution Context triple: [Golden Triangle (universities), involvesTypeOfInstitution, public research university]
-
A.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
B.
usedByInstitutionType
Indicates that something (such as a resource, tool, or service) is utilized or employed by a particular type or category of institution.
-
C.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
-
D.
establishedInstitution
Indicates that an entity founded, created, or formally set up an institution or organization.
-
E.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.