Triple
T14332731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | college of information sciences |
E355389
|
entity |
| Predicate | typicalDepartments |
P85516
|
FINISHED |
| Object | library and information science department |
—
|
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: library and information science department | Statement: [college of information sciences, typicalDepartments, library and information science department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDepartments Context triple: [college of information sciences, typicalDepartments, library and information science department]
-
A.
commonDepartments
Indicates that two or more entities share one or more of the same departments in common.
-
B.
departmentType
Indicates the classification or category of a department, specifying what kind of department it is.
-
C.
laterDepartment
Indicates that one department occurs or is considered after another in a defined ordering or sequence.
-
D.
recognizesDepartment
Indicates that one entity formally acknowledges or accepts another entity as a valid or official department.
-
E.
coversDepartment
chosen
Indicates that one entity includes, encompasses, or has responsibility for a particular department within its scope.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c1fb87c81908412c2953243c8e3 |
completed | April 14, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:13 a.m.