Knowing documents

Lauritsen, Marc

doi:10.1145/158976.159000

Cited by 12 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the most advanced form of linguistic knowledge encoded by these systems appears to be knowledge about the conditional inclusion of text segments, e.g., particular clauses in a contract. In contrast to significantly more sophisticated models of document assembly advocated by AI researchers [RML95,Lau93,GO&~], they are therefore unable to reason about the rhetorical structure and linguistic form of the documents they produce. Second, none of the systems exploit representations of domain knowledge that has any of the sophisticated inference capabilities advocated by the legal reasoning community.…”

Section: Limitations Of Current Commercial Systemsmentioning

confidence: 94%

See 1 more Smart Citation

Integrating discourse and domain knowledge for document drafting

Branting

Callaway

Mott

et al. 1999

Proceedings of the 7th International Conference on Artificial Intelligence and Law

View full text Add to dashboard Cite

Document drafting is a key component of legal expertise. Effective legal document drafting requires knowledge both of legal domain knowledge and of the structure of legal discourse. Automating the task of legal document drafting therefore requires explicit representation of both these types of knowledge. This paper proposes an architecture that integrates these two disparate knowledge sources in a modular architecture under which representation and control are optimized for each task. This architecture is being implemented in DOWPLANNER 2.0, a system for interactive document drafting.

show abstract

Section: Limitations Of Current Commercial Systemsmentioning

confidence: 94%

“…Lauritsen has suggested ihat effective automated document creation systems should provide users with a variety of inspection and editing functionalities [Lau93]. These include tools for noting essential and optional document segments.…”

Section: Introductionmentioning

confidence: 99%

Integrating discourse and domain knowledge for document drafting

Branting

Callaway

Mott

et al. 1999

Proceedings of the 7th International Conference on Artificial Intelligence and Law

View full text Add to dashboard Cite

show abstract

“…In (Lauritsen 1993) several types of knowledge involved in legal document drafting are identified. It includes knowledge that helps in presenting information the document is intended to communicate, instantiation of document class for a particular case, selecting components to build the document, applying supplementary non-legal-specific knowledge (e.g.…”

Section: Related Workmentioning

confidence: 99%

Legal document assembly system for introducing law students with legal drafting

Marković

Gostojić

2022

Artif Intell Law

View full text Add to dashboard Cite

In this paper, we present a method for introducing law students to the writing of legal documents. The method uses a machine-readable representation of the legal knowledge to support document assembly and to help the students to understand how the assembly is performed. The knowledge base consists of enacted legislation, document templates, and assembly instructions. We propose a system called LEDAS (LEgal Document Assembly System) for the interactive assembly of legal documents. It guides users through the assembly process and provides explanations of the interconnection between input data and claims stated in the document. The system acts as a platform for practicing drafting skills and has great potential as an education tool. It allows teachers to configure the system for the assembly of some particular type of legal document and then enables students to draft the documents by investigating which information is relevant for these documents and how the input data shape the final document. The generated legal document is complemented by a graphical representation of legal arguments expressed in the document. The system is based on existing legal standards to facilitate its introduction in the legal domain. Applicability of the system in the education of future lawyers is positively evaluated by the group of law students and their TA. Supplementary Information The online version contains supplementary material available at 10.1007/s10506-022-09339-2.

show abstract

“…Some progress has been made in exploiting explicit representations of the relationship between generic documents and document instances and of constraints among document components DS95]. However, there is a growing recognition in the Law and AI community that a declarative representation of the knowledge underlying the selection and con guration of textual elements is essential for the development of tools that embody the expertise of legal drafting experts Gor89,Lau93].…”

Section: Implementation and Examplementioning

confidence: 99%

Automated drafting of self-explaining documents

Branting

Lester

Callaway

1997

Proceedings of the Sixth International Conference on Artificial Intelligence and Law - ICAIL '97

View full text Add to dashboard Cite

The capacity for self-explanation can make computer-drafted documents more credible, assist in the retrieval and adaptation of archival documents, and permit comparison of documents at a deep level. We propose a knowledge-based model of documents that makes explicit the underlying goals that documents are intended to achieve and the stylistic conventions to which they must conform. These goals and conventions are expressed in a dual justi cation structure that represents the illocutionary and rhetorical dependencies underlying documents.

show abstract

Knowing documents

Cited by 12 publications

References 5 publications

Integrating discourse and domain knowledge for document drafting

Integrating discourse and domain knowledge for document drafting

Legal document assembly system for introducing law students with legal drafting

Automated drafting of self-explaining documents

Contact Info

Product

Resources

About