Triple
T70155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Computer Science, Carnegie Mellon University |
E1403
|
entity |
| Predicate | hasSubOrganization |
P747
|
FINISHED |
| Object |
Machine Learning Department, Carnegie Mellon University
The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
|
E10396
|
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: Machine Learning Department, Carnegie Mellon University | Statement: [School of Computer Science, Carnegie Mellon University, hasSubOrganization, Machine Learning Department, Carnegie Mellon University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Machine Learning Department, Carnegie Mellon University Context triple: [School of Computer Science, Carnegie Mellon University, hasSubOrganization, Machine Learning Department, Carnegie Mellon University]
-
A.
Computer Science Department, Carnegie Mellon University
The Computer Science Department at Carnegie Mellon University is a core academic unit renowned for pioneering research and education in computer science within CMU’s School of Computer Science.
-
B.
Language Technologies Institute, Carnegie Mellon University
The Language Technologies Institute at Carnegie Mellon University is a leading research and education center focused on areas such as natural language processing, machine learning for language, speech recognition, and related AI-driven language technologies.
-
C.
Computational Biology Department, Carnegie Mellon University
The Computational Biology Department at Carnegie Mellon University is an academic unit specializing in research and education at the intersection of computer science, biology, and related quantitative disciplines.
-
D.
Robotics Institute, Carnegie Mellon University
The Robotics Institute at Carnegie Mellon University is a leading research and education center dedicated to advancing the science and technology of robotics and artificial intelligence.
-
E.
Computer Science and Artificial Intelligence Laboratory (CSAIL)
The Computer Science and Artificial Intelligence Laboratory (CSAIL) is MIT’s premier research lab for computer science, artificial intelligence, and related fields, known for pioneering work in areas such as robotics, machine learning, and systems.
- 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: Machine Learning Department, Carnegie Mellon University Triple: [School of Computer Science, Carnegie Mellon University, hasSubOrganization, Machine Learning Department, Carnegie Mellon University]
Generated description
The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Machine Learning Department, Carnegie Mellon University Target entity description: The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
-
A.
Computer Science Department, Carnegie Mellon University
The Computer Science Department at Carnegie Mellon University is a core academic unit renowned for pioneering research and education in computer science within CMU’s School of Computer Science.
-
B.
Language Technologies Institute, Carnegie Mellon University
The Language Technologies Institute at Carnegie Mellon University is a leading research and education center focused on areas such as natural language processing, machine learning for language, speech recognition, and related AI-driven language technologies.
-
C.
Computational Biology Department, Carnegie Mellon University
The Computational Biology Department at Carnegie Mellon University is an academic unit specializing in research and education at the intersection of computer science, biology, and related quantitative disciplines.
-
D.
Robotics Institute, Carnegie Mellon University
The Robotics Institute at Carnegie Mellon University is a leading research and education center dedicated to advancing the science and technology of robotics and artificial intelligence.
-
E.
Computer Science and Artificial Intelligence Laboratory (CSAIL)
The Computer Science and Artificial Intelligence Laboratory (CSAIL) is MIT’s premier research lab for computer science, artificial intelligence, and related fields, known for pioneering work in areas such as robotics, machine learning, and systems.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f045d38819088f5f71e39fa1ee7 |
completed | Feb. 28, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a275e2a91c81908ec21814794d70a6 |
completed | Feb. 28, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69a276c04f308190b3089549a8bc7cec |
completed | Feb. 28, 2026, 5:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a277437a1c819086ce4faf0e913a1d |
completed | Feb. 28, 2026, 5:04 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.