Triple
T8273918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Science at the City College of New York |
E193492
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
Department of Computer Science at the City College of New York
The Department of Computer Science at the City College of New York is an academic unit offering undergraduate and graduate programs, research opportunities, and professional preparation in computer science within the college’s Division of Science.
|
E722995
|
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 Computer Science at the City College of New York | Statement: [Division of Science at the City College of New York, hasComponent, Department of Computer Science at the City College of New York]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Computer Science at the City College of New York Context triple: [Division of Science at the City College of New York, hasComponent, Department of Computer Science at the City College of New York]
-
A.
Department of Computer Science, Columbia University
The Department of Computer Science at Columbia University is a leading academic and research institution known for its contributions to theoretical computer science, systems, artificial intelligence, and interdisciplinary computing.
-
B.
Department of Computer Science, Rutgers University
The Department of Computer Science at Rutgers University is a major academic unit known for its research and education in areas such as algorithms, artificial intelligence, systems, and data science.
-
C.
Department of Computer Science (RPI)
The Department of Computer Science at Rensselaer Polytechnic Institute is a leading academic unit known for research and education in areas such as algorithms, artificial intelligence, data science, and systems within RPI’s School of Science.
-
D.
Department of Computer Science, Yale University
The Department of Computer Science at Yale University is a leading academic and research department known for its contributions to theoretical computer science, systems, and interdisciplinary computing.
-
E.
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.
- 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 Computer Science at the City College of New York Triple: [Division of Science at the City College of New York, hasComponent, Department of Computer Science at the City College of New York]
Generated description
The Department of Computer Science at the City College of New York is an academic unit offering undergraduate and graduate programs, research opportunities, and professional preparation in computer science within the college’s Division of Science.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Computer Science at the City College of New York Target entity description: The Department of Computer Science at the City College of New York is an academic unit offering undergraduate and graduate programs, research opportunities, and professional preparation in computer science within the college’s Division of Science.
-
A.
Department of Computer Science, Columbia University
The Department of Computer Science at Columbia University is a leading academic and research institution known for its contributions to theoretical computer science, systems, artificial intelligence, and interdisciplinary computing.
-
B.
Department of Computer Science, Rutgers University
The Department of Computer Science at Rutgers University is a major academic unit known for its research and education in areas such as algorithms, artificial intelligence, systems, and data science.
-
C.
Department of Computer Science (RPI)
The Department of Computer Science at Rensselaer Polytechnic Institute is a leading academic unit known for research and education in areas such as algorithms, artificial intelligence, data science, and systems within RPI’s School of Science.
-
D.
Department of Computer Science, Yale University
The Department of Computer Science at Yale University is a leading academic and research department known for its contributions to theoretical computer science, systems, and interdisciplinary computing.
-
E.
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.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb798a13388190a3610766d265a61f |
completed | March 31, 2026, 7:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd68502888819084bfe4621978711d |
completed | April 1, 2026, 6:47 p.m. |
| NEDg | Description generation | batch_69cd6c21172481908dc04b85ee4370a8 |
completed | April 1, 2026, 7:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd7e0d1b8c8190b5183cc176432061 |
completed | April 1, 2026, 8:20 p.m. |
Created at: March 30, 2026, 5:50 p.m.