Triple
T9347925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Business Administration (Cal Poly Pomona) |
E224939
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Technology and Operations Management
The Department of Technology and Operations Management is an academic unit that focuses on educating students in areas such as operations management, supply chain, and technology-driven business processes within Cal Poly Pomona’s College of Business Administration.
|
E793052
|
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 Technology and Operations Management | Statement: [College of Business Administration (Cal Poly Pomona), hasDepartment, Department of Technology and Operations Management]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Technology and Operations Management Context triple: [College of Business Administration (Cal Poly Pomona), hasDepartment, Department of Technology and Operations Management]
-
A.
Department of Operations and Information Management
The Department of Operations and Information Management is an academic unit specializing in operations management, business analytics, and information systems within the Isenberg School of Management.
-
B.
Department of Operations and Decision Sciences
The Department of Operations and Decision Sciences is an academic unit specializing in operations management, business analytics, and quantitative decision-making within the Lazaridis School of Business and Economics.
-
C.
Department of Management Systems Engineering
The Department of Management Systems Engineering is an academic unit focused on integrating engineering, management, and information systems to optimize organizational processes and decision-making.
-
D.
Department of Data Sciences and Operations
The Department of Data Sciences and Operations is an academic unit at the USC Marshall School of Business that focuses on research and education in data analytics, statistics, information systems, and operations management.
-
E.
Department of Management and Organization
The Department of Management and Organization is an academic unit at the USC Marshall School of Business that focuses on research and teaching in areas such as organizational behavior, strategy, leadership, and human resource management.
- 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 Technology and Operations Management Triple: [College of Business Administration (Cal Poly Pomona), hasDepartment, Department of Technology and Operations Management]
Generated description
The Department of Technology and Operations Management is an academic unit that focuses on educating students in areas such as operations management, supply chain, and technology-driven business processes within Cal Poly Pomona’s College of Business Administration.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Technology and Operations Management Target entity description: The Department of Technology and Operations Management is an academic unit that focuses on educating students in areas such as operations management, supply chain, and technology-driven business processes within Cal Poly Pomona’s College of Business Administration.
-
A.
Department of Operations and Information Management
The Department of Operations and Information Management is an academic unit specializing in operations management, business analytics, and information systems within the Isenberg School of Management.
-
B.
Department of Operations and Decision Sciences
The Department of Operations and Decision Sciences is an academic unit specializing in operations management, business analytics, and quantitative decision-making within the Lazaridis School of Business and Economics.
-
C.
Department of Management Systems Engineering
The Department of Management Systems Engineering is an academic unit focused on integrating engineering, management, and information systems to optimize organizational processes and decision-making.
-
D.
Department of Data Sciences and Operations
The Department of Data Sciences and Operations is an academic unit at the USC Marshall School of Business that focuses on research and education in data analytics, statistics, information systems, and operations management.
-
E.
Department of Management and Organization
The Department of Management and Organization is an academic unit within the Robert H. Smith School of Business that focuses on research and education in areas such as leadership, strategy, organizational behavior, and human resource management.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f107f0081908938f4b814eca5fc |
completed | April 1, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e432106c81908ae080f37bc80f3f |
completed | April 4, 2026, 10:13 a.m. |
| NEDg | Description generation | batch_69d0e5752a38819089b23ac52f0a6a39 |
completed | April 4, 2026, 10:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0e64cb4dc81908cef7d729d9cfb4d |
completed | April 4, 2026, 10:22 a.m. |
Created at: March 30, 2026, 7:41 p.m.