Triple
T12157631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Johnson |
E289617
|
entity |
| Predicate | workInstitution |
P1203
|
FINISHED |
| Object |
University of Illinois at Urbana-Champaign Department of Computer Science
The University of Illinois at Urbana-Champaign Department of Computer Science is a leading academic and research department known for its pioneering contributions to computer science education, theory, and technology.
|
E963766
|
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: University of Illinois at Urbana-Champaign Department of Computer Science | Statement: [Ralph Johnson, workInstitution, University of Illinois at Urbana-Champaign Department of Computer Science]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: University of Illinois at Urbana-Champaign Department of Computer Science Context triple: [Ralph Johnson, workInstitution, University of Illinois at Urbana-Champaign Department of Computer Science]
-
A.
Department of Computer Science at the University of Chicago
The Department of Computer Science at the University of Chicago is a leading academic unit known for its rigorous theoretical foundations, innovative research in areas such as machine learning, systems, and programming languages, and strong interdisciplinary collaborations across the university.
-
B.
Department of Computer Science (Purdue University)
The Department of Computer Science at Purdue University is a leading academic department known for its strong research and education programs in areas such as systems, security, artificial intelligence, and software engineering.
-
C.
Cornell University Department of Computer Science
Cornell University Department of Computer Science is a leading academic department known for its pioneering research and education in areas such as theory, systems, artificial intelligence, and programming languages.
-
D.
Department of Computer Sciences (University of Wisconsin–Madison)
The Department of Computer Sciences at the University of Wisconsin–Madison is a leading academic department renowned for its research and education in areas such as systems, theory, artificial intelligence, and data science.
-
E.
Department of Computer Science, UC Davis
The Department of Computer Science at UC Davis is an academic unit of the University of California, Davis, focused on education and research in computer science and related fields.
- 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: University of Illinois at Urbana-Champaign Department of Computer Science Triple: [Ralph Johnson, workInstitution, University of Illinois at Urbana-Champaign Department of Computer Science]
Generated description
The University of Illinois at Urbana-Champaign Department of Computer Science is a leading academic and research department known for its pioneering contributions to computer science education, theory, and technology.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: University of Illinois at Urbana-Champaign Department of Computer Science Target entity description: The University of Illinois at Urbana-Champaign Department of Computer Science is a leading academic and research department known for its pioneering contributions to computer science education, theory, and technology.
-
A.
Department of Computer Science at the University of Chicago
The Department of Computer Science at the University of Chicago is a leading academic unit known for its rigorous theoretical foundations, innovative research in areas such as machine learning, systems, and programming languages, and strong interdisciplinary collaborations across the university.
-
B.
Department of Computer Science (Purdue University)
The Department of Computer Science at Purdue University is a leading academic department known for its strong research and education programs in areas such as systems, security, artificial intelligence, and software engineering.
-
C.
Cornell University Department of Computer Science
Cornell University Department of Computer Science is a leading academic department known for its pioneering research and education in areas such as theory, systems, artificial intelligence, and programming languages.
-
D.
Department of Computer Sciences (University of Wisconsin–Madison)
The Department of Computer Sciences at the University of Wisconsin–Madison is a leading academic department renowned for its research and education in areas such as systems, theory, artificial intelligence, and data science.
-
E.
Department of Computer Science, UC Davis
The Department of Computer Science at UC Davis is an academic unit of the University of California, Davis, focused on education and research in computer science and related fields.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c277e481908351bf4e664dda42 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f69c8d408190abbc900deb534045 |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f5fe53d47c8190896a9abf8cc4bc31 |
completed | May 2, 2026, 1:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5ffc563a08190b95db768df475a3a |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 8, 2026, 9:50 p.m.