2010
DOI: 10.1007/978-3-642-16524-5_7
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When a FrameNet-Style Knowledge Description Meets an Ontological Characterization of Fundamental Legal Concepts

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Cited by 12 publications
(8 citation statements)
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“…To these figures we must add internal regulations of firms. In Italy each bank employee is expected to know 6,000 pages of internal regulations 1 . Paper-based methods of researching laws and regulations are no longer fit for purpose.…”
Section: Growth Of the Lawmentioning
confidence: 99%
See 1 more Smart Citation
“…To these figures we must add internal regulations of firms. In Italy each bank employee is expected to know 6,000 pages of internal regulations 1 . Paper-based methods of researching laws and regulations are no longer fit for purpose.…”
Section: Growth Of the Lawmentioning
confidence: 99%
“…Agnoloni et al [1]'s FrameNet ontology departs from the WordNet structure, emphasising that meaning depends on "under which Circumstances, which State of affairs is sanctioned under which Principle". Like the Legal Taxonomy Syllabus ontology, Agnoloni et al [1] separate concepts from terms.…”
Section: Related Workmentioning
confidence: 99%
“…Like the Legal Taxonomy Syllabus ontology, Agnoloni et al [1] separate concepts from terms. However, unlike Legal Taxonomy Syllabus they assume that translated terms are exact and that equivalent multilingual terms map onto the same concept.…”
Section: Related Workmentioning
confidence: 99%
“…SALSA project (Burchardt et al, 2009) applies the FrameNet semantic tags to manually annotating a German corpus and automatically developing a frame-based lexicon of German. Other works have applied FrameNet frames to automatic development of lexicons using automatic transfer of corpus annotation in parallel corpora (Padó and Lapata, 2005), (Padó and Lapata, 2009), (Tonelli and Pianta, 2008) and for legal ontology improvement (Agnoloni et al, 2009). The objective of this paper is to evaluate the applicability of Frame Semantics theory and FrameNet paradigm for the semantic annotation of legal texts.…”
Section: Introductionmentioning
confidence: 99%