Triple
T432355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George R. Brown School of Engineering |
E9740
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Materials Science and NanoEngineering
The Department of Materials Science and NanoEngineering is an academic unit specializing in the study and engineering of materials and nanoscale systems, offering research and education in areas such as nanotechnology, advanced materials, and related engineering applications.
|
E54222
|
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 Materials Science and NanoEngineering | Statement: [George R. Brown School of Engineering, hasDepartment, Department of Materials Science and NanoEngineering]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Materials Science and NanoEngineering Context triple: [George R. Brown School of Engineering, hasDepartment, Department of Materials Science and NanoEngineering]
-
A.
Department of Materials Science and Engineering (Carnegie Mellon University)
The Department of Materials Science and Engineering at Carnegie Mellon University is an academic unit specializing in the study, research, and education of materials and their applications in engineering and technology.
-
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.
Institute for Materials Research
The Institute for Materials Research is a leading Japanese research center at Tohoku University specializing in advanced materials science and engineering.
-
D.
Division of Materials Chemistry
The Division of Materials Chemistry is a specialized unit of the American Chemical Society that focuses on advancing research, education, and collaboration in the field of materials chemistry.
-
E.
Division of Polymeric Materials: Science and Engineering
The Division of Polymeric Materials: Science and Engineering is a professional subdivision of the American Chemical Society that focuses on the science, engineering, and technological applications of polymeric materials.
- 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 Materials Science and NanoEngineering Triple: [George R. Brown School of Engineering, hasDepartment, Department of Materials Science and NanoEngineering]
Generated description
The Department of Materials Science and NanoEngineering is an academic unit specializing in the study and engineering of materials and nanoscale systems, offering research and education in areas such as nanotechnology, advanced materials, and related engineering applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Materials Science and NanoEngineering Target entity description: The Department of Materials Science and NanoEngineering is an academic unit specializing in the study and engineering of materials and nanoscale systems, offering research and education in areas such as nanotechnology, advanced materials, and related engineering applications.
-
A.
Department of Materials Science and Engineering (Carnegie Mellon University)
The Department of Materials Science and Engineering at Carnegie Mellon University is an academic unit specializing in the study, research, and education of materials and their applications in engineering and technology.
-
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.
Institute for Materials Research
The Institute for Materials Research is a leading Japanese research center at Tohoku University specializing in advanced materials science and engineering.
-
D.
Division of Materials Chemistry
The Division of Materials Chemistry is a specialized unit of the American Chemical Society that focuses on advancing research, education, and collaboration in the field of materials chemistry.
-
E.
Division of Polymeric Materials: Science and Engineering
The Division of Polymeric Materials: Science and Engineering is a professional subdivision of the American Chemical Society that focuses on the science, engineering, and technological applications of polymeric materials.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eef07e748190b05392778f3de980 |
completed | Feb. 28, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a42f6a359081909c27b9e382633aa8 |
completed | March 1, 2026, 12:22 p.m. |
| NEDg | Description generation | batch_69a4302e3a7c81909cb717f13b5fe74d |
completed | March 1, 2026, 12:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a430c72ff88190ad48e4b2d1f21f43 |
completed | March 1, 2026, 12:27 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.