Triple
T5170039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Pennsylvania Department of Linguistics |
E116653
|
entity |
| Predicate | collaboratesWith |
P37
|
FINISHED |
| Object |
Computer and Information Science Department, University of Pennsylvania
The Computer and Information Science Department at the University of Pennsylvania is a leading academic unit known for its research and education in computer science, artificial intelligence, and related fields within the School of Engineering and Applied Science.
|
E499685
|
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: Computer and Information Science Department, University of Pennsylvania | Statement: [University of Pennsylvania Department of Linguistics, collaboratesWith, Computer and Information Science Department, University of Pennsylvania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Computer and Information Science Department, University of Pennsylvania Context triple: [University of Pennsylvania Department of Linguistics, collaboratesWith, Computer and Information Science Department, University of Pennsylvania]
-
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.
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.
School of Computer Science at Carnegie Mellon University
The School of Computer Science at Carnegie Mellon University is a world-renowned academic and research institution recognized for pioneering contributions across computer science, artificial intelligence, robotics, and related fields.
-
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.
Institute for Software Research, Carnegie Mellon University
The Institute for Software Research at Carnegie Mellon University is a leading academic center focused on research and education in software engineering, cybersecurity, privacy, and socio-technical 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: Computer and Information Science Department, University of Pennsylvania Triple: [University of Pennsylvania Department of Linguistics, collaboratesWith, Computer and Information Science Department, University of Pennsylvania]
Generated description
The Computer and Information Science Department at the University of Pennsylvania is a leading academic unit known for its research and education in computer science, artificial intelligence, and related fields within the School of Engineering and Applied Science.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Computer and Information Science Department, University of Pennsylvania Target entity description: The Computer and Information Science Department at the University of Pennsylvania is a leading academic unit known for its research and education in computer science, artificial intelligence, and related fields within the School of Engineering and Applied Science.
-
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.
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.
School of Computer Science at Carnegie Mellon University
The School of Computer Science at Carnegie Mellon University is a world-renowned academic and research institution recognized for pioneering contributions across computer science, artificial intelligence, robotics, and related fields.
-
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.
Institute for Software Research, Carnegie Mellon University
The Institute for Software Research at Carnegie Mellon University is a leading academic center focused on research and education in software engineering, cybersecurity, privacy, and socio-technical 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd794f44248190a3a90c92208104a7 |
completed | March 20, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed93f33ac8190b2f60a8e95685bc8 |
completed | March 21, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69beda0419108190862d028a14227e8a |
completed | March 21, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bedaa232ac81908c5ee2d4ba8cbcd7 |
completed | March 21, 2026, 5:51 p.m. |
Created at: March 20, 2026, 1:45 p.m.