Triple

T6880402
Position Surface form Disambiguated ID Type / Status
Subject Donald Bren School of Information and Computer Sciences E158777 entity
Predicate hasAcademicUnit P1488 FINISHED
Object Department of Statistics
The Department of Statistics is an academic unit within the Donald Bren School of Information and Computer Sciences that focuses on statistical theory, methods, and their applications in data analysis and related fields.
E625020 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 | Statement: [Donald Bren School of Information and Computer Sciences, hasAcademicUnit, Department of Statistics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Statistics
Context triple: [Donald Bren School of Information and Computer Sciences, hasAcademicUnit, Department of Statistics]
  • A. Department of Statistics
    The Department of Statistics at the National University of Colombia (Bogotá) is an academic unit dedicated to teaching, research, and professional training in statistical science and its applications.
  • B. Department of Statistics
    The Department of Statistics is an academic unit within Alexandria University's Faculty of Commerce that specializes in teaching and research in statistical theory and its applications in business and economics.
  • 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. Department of Statistics
    The Department of Statistics at the University of Warwick is a leading academic department specializing in statistical theory, methodology, and applications, known for its strong research output and high-quality teaching.
  • 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
Triple: [Donald Bren School of Information and Computer Sciences, hasAcademicUnit, Department of Statistics]
Generated description
The Department of Statistics is an academic unit within the Donald Bren School of Information and Computer Sciences that focuses on statistical theory, methods, and their applications in data analysis and related fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Statistics
Target entity description: The Department of Statistics is an academic unit within the Donald Bren School of Information and Computer Sciences that focuses on statistical theory, methods, and their applications in data analysis and related fields.
  • A. Department of Statistics
    The Department of Statistics is an academic unit specializing in statistical theory, methods, and applications within the broader Faculty of Mathematics, Informatics and Statistics.
  • B. Department of Statistics
    The Department of Statistics is an academic unit specializing in statistical theory, methods, and applications within the Physical Sciences Division.
  • C. 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.
  • D. Department of Statistics
    The Department of Statistics is an academic unit within Alexandria University's Faculty of Commerce that specializes in teaching and research in statistical theory and its applications in business and economics.
  • E. Department of Statistics
    The Department of Statistics at Savitribai Phule Pune University is an academic unit dedicated to education and research in statistical theory, methods, and applications.
  • 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_69c688342f6c8190ad7eea6ba262db99 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8e60f94819086315b1dd2ea7a3e completed March 27, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c742c999cc8190a14aa0ae6c7a1f54 completed March 28, 2026, 2:54 a.m.
NEDg Description generation batch_69c743dffc188190a59ca6c86483c348 completed March 28, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69c7444e57a881908808a4bd96505048 completed March 28, 2026, 3 a.m.
Created at: March 27, 2026, 2:23 p.m.