Triple
T1797128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persi Diaconis |
E39629
|
entity |
| Predicate | workInstitution |
P1203
|
FINISHED |
| Object |
Stanford University Department of Statistics
The Stanford University Department of Statistics is a leading academic department renowned for its research and teaching in probability, statistics, and data science.
|
E201333
|
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: Stanford University Department of Statistics | Statement: [Persi Diaconis, workInstitution, Stanford University Department of Statistics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanford University Department of Statistics Context triple: [Persi Diaconis, workInstitution, Stanford University Department of Statistics]
-
A.
Department of Statistics (UC Berkeley)
The Department of Statistics at UC Berkeley is a leading academic department renowned for its pioneering research and education in statistics, probability, and data science.
-
B.
Department of Statistics
The Department of Statistics is an academic unit within Rice University's George R. Brown School of Engineering that focuses on education and research in statistical theory, methods, and applications.
-
C.
Department of Statistics
The Department of Statistics is an academic unit at Cairo University's Faculty of Commerce that specializes in teaching and research in statistical theory and its applications in business and economics.
-
D.
Department of Statistics
The Department of Statistics at Presidency College, Kolkata is an academic unit specializing in teaching and research in statistical theory and its applications.
-
E.
Stanford Computer Science Department
The Stanford Computer Science Department is a leading academic department at Stanford University renowned for its pioneering research and education in computer science and its close ties to Silicon Valley innovation.
- 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: Stanford University Department of Statistics Triple: [Persi Diaconis, workInstitution, Stanford University Department of Statistics]
Generated description
The Stanford University Department of Statistics is a leading academic department renowned for its research and teaching in probability, statistics, and data science.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stanford University Department of Statistics Target entity description: The Stanford University Department of Statistics is a leading academic department renowned for its research and teaching in probability, statistics, and data science.
-
A.
Department of Statistics (UC Berkeley)
The Department of Statistics at UC Berkeley is a leading academic department renowned for its pioneering research and education in statistics, probability, and data science.
-
B.
Department of Statistics
The Department of Statistics is an academic unit within Rice University's George R. Brown School of Engineering that focuses on education and research in statistical theory, methods, and applications.
-
C.
Department of Statistics
The Department of Statistics is an academic unit at Cairo University's Faculty of Commerce that specializes in teaching and research in statistical theory and its applications in business and economics.
-
D.
Department of Statistics
The Department of Statistics at Presidency College, Kolkata is an academic unit specializing in teaching and research in statistical theory and its applications.
-
E.
Stanford Computer Science Department
The Stanford Computer Science Department is a leading academic department at Stanford University renowned for its pioneering research and education in computer science and its close ties to Silicon Valley innovation.
- 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa6566cd808190a67f33ad47d8ca8e |
completed | March 6, 2026, 5:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5d6cee88190b26814134037aba6 |
completed | March 8, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69adb8b626688190b4953d4549339dea |
completed | March 8, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb9253fa08190bfb7d245208150c0 |
completed | March 8, 2026, 6 p.m. |
Created at: March 4, 2026, 7:32 p.m.