Triple
T912367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahen Centre for Information Technology |
E19688
|
entity |
| Predicate | housesAcademicUnit |
P589
|
FINISHED |
| Object | Department of Computer Science, University of Toronto |
E83526
|
NE FINISHED |
How this triple was built (3 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: Department of Computer Science, University of Toronto | Statement: [Bahen Centre for Information Technology, housesAcademicUnit, Department of Computer Science, University of Toronto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Computer Science, University of Toronto Context triple: [Bahen Centre for Information Technology, housesAcademicUnit, Department of Computer Science, University of Toronto]
-
A.
University of Toronto Department of Computer Science
chosen
The University of Toronto Department of Computer Science is a leading global center for research and education in computer science, known for its pioneering contributions to areas such as machine learning, artificial intelligence, and theoretical computer science.
-
B.
Computer Science Department, Carnegie Mellon University
The Computer Science Department at Carnegie Mellon University is a core academic unit renowned for pioneering research and education in computer science within CMU’s School of Computer Science.
-
C.
Department of Computer Science, UCLA
The Department of Computer Science at UCLA is a leading academic and research department known for pioneering contributions to computer networking, algorithms, artificial intelligence, and systems within a top-tier public university.
-
D.
Department of Computer Science and Technology, University of Cambridge
The Department of Computer Science and Technology at the University of Cambridge is a leading academic and research centre in computer science, renowned for its pioneering contributions to computing theory, systems, and applications.
-
E.
School of Computer Science
The School of Computer Science at Wuhan University is an academic unit specializing in computer science education and research within the university.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: housesAcademicUnit Context triple: [Bahen Centre for Information Technology, housesAcademicUnit, Department of Computer Science, University of Toronto]
-
A.
hasAcademicUnit
Indicates that an entity is associated with, or belongs to, a specific academic unit such as a department, school, or faculty within an educational institution.
-
B.
hasAcademicDepartment
chosen
Indicates that an institution or organization includes or is associated with a specific academic department.
-
C.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
D.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
E.
publicUniversityFaculty
Indicates that a person is a member of the faculty (e.g., professor, lecturer, instructor) at a public university.
- F. None of above.
Provenance (4 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf5e59588190b9d2bb00adf5c871 |
completed | March 4, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.