Triple
T350307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Engineering, University of California, Berkeley |
E7426
|
entity |
| Predicate | hasAcademicUnit |
P1488
|
FINISHED |
| Object |
Department of Industrial Engineering and Operations Research, UC Berkeley
The Department of Industrial Engineering and Operations Research at UC Berkeley is a leading academic department specializing in optimization, stochastic processes, data analytics, and systems engineering for complex decision-making in industry and society.
|
E44990
|
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 Industrial Engineering and Operations Research, UC Berkeley | Statement: [College of Engineering, University of California, Berkeley, hasAcademicUnit, Department of Industrial Engineering and Operations Research, UC Berkeley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Industrial Engineering and Operations Research, UC Berkeley Context triple: [College of Engineering, University of California, Berkeley, hasAcademicUnit, Department of Industrial Engineering and Operations Research, UC Berkeley]
-
A.
Department of Electrical Engineering and Computer Sciences, UC Berkeley
The Department of Electrical Engineering and Computer Sciences at UC Berkeley is a leading academic department renowned for its pioneering research and top-ranked programs in electrical engineering, computer science, and related fields.
-
B.
Department of Materials Science and Engineering, UC Berkeley
The Department of Materials Science and Engineering at UC Berkeley is a leading academic department focused on the study, design, and engineering of materials for advanced technologies and scientific innovation.
-
C.
UC Berkeley I School
UC Berkeley I School is the University of California, Berkeley’s graduate school focused on information science, data science, and technology policy.
-
D.
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.
-
E.
Department of Engineering and Public Policy (Carnegie Mellon University)
The Department of Engineering and Public Policy at Carnegie Mellon University is an interdisciplinary academic unit that integrates engineering, social science, and policy analysis to address complex societal and technological challenges.
- 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 Industrial Engineering and Operations Research, UC Berkeley Triple: [College of Engineering, University of California, Berkeley, hasAcademicUnit, Department of Industrial Engineering and Operations Research, UC Berkeley]
Generated description
The Department of Industrial Engineering and Operations Research at UC Berkeley is a leading academic department specializing in optimization, stochastic processes, data analytics, and systems engineering for complex decision-making in industry and society.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Industrial Engineering and Operations Research, UC Berkeley Target entity description: The Department of Industrial Engineering and Operations Research at UC Berkeley is a leading academic department specializing in optimization, stochastic processes, data analytics, and systems engineering for complex decision-making in industry and society.
-
A.
Department of Electrical Engineering and Computer Sciences, UC Berkeley
The Department of Electrical Engineering and Computer Sciences at UC Berkeley is a leading academic department renowned for its pioneering research and top-ranked programs in electrical engineering, computer science, and related fields.
-
B.
Department of Materials Science and Engineering, UC Berkeley
The Department of Materials Science and Engineering at UC Berkeley is a leading academic department focused on the study, design, and engineering of materials for advanced technologies and scientific innovation.
-
C.
UC Berkeley I School
UC Berkeley I School is the University of California, Berkeley’s graduate school focused on information science, data science, and technology policy.
-
D.
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.
-
E.
Department of Engineering and Public Policy (Carnegie Mellon University)
The Department of Engineering and Public Policy at Carnegie Mellon University is an interdisciplinary academic unit that integrates engineering, social science, and policy analysis to address complex societal and technological challenges.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb1f028c819098fa6480b4ca5cf0 |
completed | Feb. 28, 2026, 1:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e0165b6481909345301df3f2144d |
completed | March 1, 2026, 6:43 a.m. |
| NEDg | Description generation | batch_69a3e07452388190a8162c327c76185b |
completed | March 1, 2026, 6:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3e17d43f4819081500e106d3973e9 |
completed | March 1, 2026, 6:49 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.