Name
Abstract | ||
|---|---|---|
This article seeks to address the problem of the 'resource consumption bottleneck' of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in a legal document management system. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/s10506-020-09271-3 | ARTIFICIAL INTELLIGENCE AND LAW |
Keywords | DocType | Volume |
Classification, Information extraction, Ontology, Normative reasoning, Semantic role labeling, Artificial intelligence, Law | Journal | 29 |
Issue | ISSN | Citations |
2 | 0924-8463 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Llio Humphreys | 1 | 73 | 8.76 |
| Guido Boella | 2 | 1867 | 162.59 |
| Leendert van der Torre | 3 | 2930 | 224.99 |
| Livio Robaldo | 4 | 269 | 33.46 |
| Luigi Di Caro | 5 | 195 | 35.21 |
| Sepideh Ghanavati | 6 | 416 | 26.40 |
| Robert Muthuri | 7 | 12 | 2.80 |