Triple
T8656725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cary Coglianese |
E205437
|
entity |
| Predicate | founderOf |
P104
|
FINISHED |
| Object |
Penn Program on Regulation
The Penn Program on Regulation is a research and policy initiative at the University of Pennsylvania focused on improving the design, implementation, and understanding of regulatory systems across diverse sectors.
|
E748732
|
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: Penn Program on Regulation | Statement: [Cary Coglianese, founderOf, Penn Program on Regulation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penn Program on Regulation Context triple: [Cary Coglianese, founderOf, Penn Program on Regulation]
-
A.
Law and Economics Program
The Law and Economics Program is an interdisciplinary academic initiative that integrates legal studies with economic theory and quantitative methods to analyze and inform law and public policy.
-
B.
Reports on the relation of transportation regulation to corporate power
"Reports on the relation of transportation regulation to corporate power" is an investigative study by the U.S. Bureau of Corporations analyzing how government oversight of transportation affects the influence and practices of large corporations.
-
C.
Harvard school of antitrust
The Harvard school of antitrust is a traditional legal-economic approach to competition law that emphasizes market structure, concentration, and potential harms to competitors as key indicators of anticompetitive behavior.
-
D.
Cornell e-Rulemaking Initiative
The Cornell e-Rulemaking Initiative is a research and policy center that develops and studies online tools to improve public participation and transparency in the federal rulemaking process.
-
E.
Coase-Sandor Institute for Law and Economics
The Coase-Sandor Institute for Law and Economics is a research center at the University of Chicago Law School dedicated to advancing the study and application of economic principles in legal scholarship and policy.
- 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: Penn Program on Regulation Triple: [Cary Coglianese, founderOf, Penn Program on Regulation]
Generated description
The Penn Program on Regulation is a research and policy initiative at the University of Pennsylvania focused on improving the design, implementation, and understanding of regulatory systems across diverse sectors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Penn Program on Regulation Target entity description: The Penn Program on Regulation is a research and policy initiative at the University of Pennsylvania focused on improving the design, implementation, and understanding of regulatory systems across diverse sectors.
-
A.
Law and Economics Program
The Law and Economics Program is an interdisciplinary academic initiative that integrates legal studies with economic theory and quantitative methods to analyze and inform law and public policy.
-
B.
Reports on the relation of transportation regulation to corporate power
"Reports on the relation of transportation regulation to corporate power" is an investigative study by the U.S. Bureau of Corporations analyzing how government oversight of transportation affects the influence and practices of large corporations.
-
C.
Harvard school of antitrust
The Harvard school of antitrust is a traditional legal-economic approach to competition law that emphasizes market structure, concentration, and potential harms to competitors as key indicators of anticompetitive behavior.
-
D.
Cornell e-Rulemaking Initiative
The Cornell e-Rulemaking Initiative is a research and policy center that develops and studies online tools to improve public participation and transparency in the federal rulemaking process.
-
E.
Coase-Sandor Institute for Law and Economics
The Coase-Sandor Institute for Law and Economics is a research center at the University of Chicago Law School dedicated to advancing the study and application of economic principles in legal scholarship and policy.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484569788190aa41395854684e6f |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccec941881908263cd3205f10ccd |
completed | April 2, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69cece8c4bdc8190988990c675f50f86 |
completed | April 2, 2026, 8:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecf3a0e78819082cc7c43eceae309 |
completed | April 2, 2026, 8:19 p.m. |
Created at: March 30, 2026, 6:30 p.m.