Triple
T13267025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radford M. Neal |
E315948
|
entity |
| Predicate | workInstitution |
P1203
|
FINISHED |
| Object |
Department of Statistics, University of Toronto
The Department of Statistics at the University of Toronto is a leading academic unit specializing in statistical research and education within one of Canada’s top universities.
|
E1031258
|
NE FINISHED |
How this triple was built (4 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 Statistics, University of Toronto | Statement: [Radford M. Neal, workInstitution, Department of Statistics, University of Toronto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Statistics, University of Toronto Context triple: [Radford M. Neal, workInstitution, Department of Statistics, University of Toronto]
-
A.
Department of Statistics (University of British Columbia)
The Department of Statistics at the University of British Columbia is an academic unit specializing in teaching and research in statistical science, data analysis, and related quantitative methods.
-
B.
Department of Statistics, University of Oxford
The Department of Statistics at the University of Oxford is a leading academic center for research and teaching in statistics, probability, and data science, renowned for its contributions to both theoretical and applied statistical methodology.
-
C.
Department of Statistics and Actuarial Science, University of Waterloo
The Department of Statistics and Actuarial Science at the University of Waterloo is a leading academic unit renowned for its research and education in statistics, actuarial science, data science, and related quantitative fields.
-
D.
Department of Applied Statistics at University College London
The Department of Applied Statistics at University College London was an influential early 20th-century center for the development of modern statistical theory and methods under the leadership of pioneering statistician Karl Pearson.
-
E.
Department of Statistics (Purdue University)
The Department of Statistics at Purdue University is a leading academic department known for its research and education in statistical theory, methodology, and applications across diverse scientific fields.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Department of Statistics, University of Toronto Triple: [Radford M. Neal, workInstitution, Department of Statistics, University of Toronto]
Generated description
The Department of Statistics at the University of Toronto is a leading academic unit specializing in statistical research and education within one of Canada’s top universities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Statistics, University of Toronto Target entity description: The Department of Statistics at the University of Toronto is a leading academic unit specializing in statistical research and education within one of Canada’s top universities.
-
A.
Department of Statistics (University of British Columbia)
The Department of Statistics at the University of British Columbia is an academic unit specializing in teaching and research in statistical science, data analysis, and related quantitative methods.
-
B.
Department of Statistics, University of Oxford
The Department of Statistics at the University of Oxford is a leading academic center for research and teaching in statistics, probability, and data science, renowned for its contributions to both theoretical and applied statistical methodology.
-
C.
Department of Statistics and Actuarial Science, University of Waterloo
The Department of Statistics and Actuarial Science at the University of Waterloo is a leading academic unit renowned for its research and education in statistics, actuarial science, data science, and related quantitative fields.
-
D.
Department of Applied Statistics at University College London
The Department of Applied Statistics at University College London was an influential early 20th-century center for the development of modern statistical theory and methods under the leadership of pioneering statistician Karl Pearson.
-
E.
Department of Statistics (Purdue University)
The Department of Statistics at Purdue University is a leading academic department known for its research and education in statistical theory, methodology, and applications across diverse scientific fields.
- F. None of above. chosen
Provenance (5 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9901e44bc8190966f87ae219d6bf4 |
completed | April 11, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a4cc20881909b1ca6623e5b1988 |
completed | May 3, 2026, 8:41 a.m. |
| NEDg | Description generation | batch_69f70bc5111c8190ae5b098c806bb845 |
completed | May 3, 2026, 8:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70ca343f08190b6484f464ed40810 |
completed | May 3, 2026, 8:51 a.m. |
Created at: April 9, 2026, 9:25 p.m.