Triple
T1694889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wittenberg University |
E36633
|
entity |
| Predicate | hasInstitutionType |
P303
|
FINISHED |
| Object | four-year college |
—
|
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: four-year college | Statement: [Wittenberg University, hasInstitutionType, four-year college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInstitutionType Context triple: [Wittenberg University, hasInstitutionType, four-year college]
-
A.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
B.
hasKeyInstitutionType
Indicates that an entity is associated with a specific type or category of key institution.
-
C.
associatedInstitutionType
Indicates the type or category of institution with which an entity is associated.
-
D.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
-
E.
recognizedAsInstitutionBy
Indicates that an entity is acknowledged or accepted as an institution by a specified recognizing party.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf169da888190b3aa334752f1952b |
completed | March 6, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69aa61b8ce348190b46154af0b041ff0 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.