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See detailAN NLP-BASED FRAMEWORK TO FACILITATE THE DERIVATION OF LEGAL REQUIREMENTS FROM LEGAL TEXTS
Sleimi, Amin UL

Doctoral thesis (2020)

Information systems in several regulated domains (e.g., healthcare, taxation, labor) must comply with the applicable laws and regulations. In order to demonstrate compliance, several techniques can be ... [more ▼]

Information systems in several regulated domains (e.g., healthcare, taxation, labor) must comply with the applicable laws and regulations. In order to demonstrate compliance, several techniques can be used for assessing that such systems meet their specified legal requirements. Since requirements analysts do not have the required legal expertise, they often rely on the advisory of legal professionals. Hence, this paramount activity is expensive as it involves numerous professionals. Add to this, the communication gap between all the involved stakeholders: legal professionals, requirements analysts and software engineers. Several techniques attempt to bridge this communication gap by streamlining this process. A promising way to do so is through the automation of legal semantic metadata extraction and legal requirements elicitation from legal texts. Typically, one has to search legal texts for the relevant information for the IT system at hand, extract the legal requirements entailed by these legal statements that are pertinent to the IT system, and validate the conclusiveness and correctness of the finalized set of legal requirements. Nevertheless, the automation of legal text processing raises several challenges, especially when applied to IT systems. Existing Natural Language Processing (NLP) techniques are not built to handle the peculiarities of legal texts. On the one hand, NLP techniques are far from perfect in handling several linguistic phenomena such as anaphora, word sense disambiguation and delineating the addressee of the sentence. Add to that, the performance of these NLP techniques decreases when applied to foreign languages (other than English). On the other hand, legal text is far from being identical to the formal language used in journalism. We note that the most prominent NLP techniques are developed and tested against a selection of newspapers articles. In addition, legal text introduces cross-references and legalese that are paramount to proper legal analysis. Besides, there is still some work to be done concerning topicalization, which we need to consider for the relevance of legal statements. Existing techniques for streamlining the compliance checking of IT systems often rely on code-like artifacts with no intuitive appeal to legal professionals. Subsequently, one has no practical way to double-check with legal professionals that the elicited legal requirements are indeed correct and complete regarding the IT system at hand. Further, manually eliciting the legal requirements is an expensive, tedious and error-prone activity. The challenge is to propose a suitable knowledge representation that can be easily understood by all the involved stakeholders but at the same time remains cohesive and conclusive enough to enable the automation of legal requirements elicitation. In this dissertation, we investigate to which extent one can automate legal processing in the Requirements Engineering context. We focus exclusively on legal requirements elicitation for IT systems that have to conform to prescriptive regulations. All our technical solutions have been developed and empirically evaluated in close collaboration with a government entity. [less ▲]

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See detailAutomated Recommendation of Templates for Legal Requirements
Sleimi, Amin UL; Ceci, Marcello UL; Sabetzadeh, Mehrdad UL et al

in Proceedings of the 28th IEEE International Requirements Engineering Conference (RE'20) (2020)

[Context] In legal requirements elicitation, requirements analysts need to extract obligations from legal texts. However, legal texts often express obligations only indirectly, for example, by attributing ... [more ▼]

[Context] In legal requirements elicitation, requirements analysts need to extract obligations from legal texts. However, legal texts often express obligations only indirectly, for example, by attributing a right to the counterpart. This phenomenon has already been described in the Requirements Engineering (RE) literature. [Objectives] We investigate the use of requirements templates for the systematic elicitation of legal requirements. Our work is motivated by two observations: (1) The existing literature does not provide a harmonized view on the requirements templates that are useful for legal RE; (2) Despite the promising recent advancements in natural language processing (NLP), automated support for legal RE through the suggestion of requirements templates has not been achieved yet. Our objective is to take steps toward addressing these limitations. [Methods] We review and reconcile the legal requirement templates proposed in RE. Subsequently, we conduct a qualitative study to define NLP rules for template recommendation. [Results and Conclusions] Our contributions consist of (a) a harmonized list of requirements templates pertinent to legal RE, and (b) rules for the automatic recommendation of such templates. We evaluate our rules through a case study on 400 statements from two legal domains. The results indicate a recall and precision of 82,3% and 79,8%, respectively. We show that introducing some limited interaction with the analyst considerably improves accuracy. Specifically, our human-feedback strategy increases recall by 12% and precision by 10,8%, thus yielding an overall recall of 94,3% and overall precision of 90,6%. [less ▲]

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See detailA Query System for Extracting Requirements-related Information from Legal Texts
Sleimi, Amin UL; Ceci, Marcello UL; Sannier, Nicolas UL et al

in Proceedings of the 27th IEEE International Requirements Engineering Conference (RE'19), pp. 319-329 (2019)

Searching legal texts for relevant information is a complex and expensive activity. The search solutions offered by present-day legal portals are targeted primarily at legal professionals. These solutions ... [more ▼]

Searching legal texts for relevant information is a complex and expensive activity. The search solutions offered by present-day legal portals are targeted primarily at legal professionals. These solutions are not adequate for requirements analysts whose objective is to extract domain knowledge including stakeholders, rights and duties, and business processes that are relevant to legal requirements. Semantic Web technologies now enable smart search capabilities and can be exploited to help requirements analysts in elaborating legal requirements. In our previous work, we developed an automated framework for extracting semantic metadata from legal texts. In this paper, we investigate the use of our metadata extraction framework as an enabler for smart legal search with a focus on requirements engineering activities. We report on our industrial experience helping the Government of Luxembourg provide an advanced search facility over Luxembourg’s Income Tax Law. The experience shows that semantic legal metadata can be successfully exploited for answering requirements engineering-related legal queries. Our results also suggest that our conceptualization of semantic legal metadata can be further improved with new information elements and relations. [less ▲]

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See detailAutomated Extraction of Semantic Legal Metadata Using Natural Language Processing
Sleimi, Amin UL; Sannier, Nicolas UL; Sabetzadeh, Mehrdad UL et al

in the 26th IEEE International Requirements Engineering Conference, Banff, Alberta, 20-24 August 2018 (2018, August)

[Context] Semantic legal metadata provides information that helps with understanding and interpreting the meaning of legal provisions. Such metadata is important for the systematic analysis of legal ... [more ▼]

[Context] Semantic legal metadata provides information that helps with understanding and interpreting the meaning of legal provisions. Such metadata is important for the systematic analysis of legal requirements. [Objectives] Our work is motivated by two observations: (1) The existing requirements engineering (RE) literature does not provide a harmonized view on the semantic metadata types that are useful for legal requirements analysis. (2) Automated support for the extraction of semantic legal metadata is scarce, and further does not exploit the full potential of natural language processing (NLP). Our objective is to take steps toward addressing these limitations. [Methods] We review and reconcile the semantic legal metadata types proposed in RE. Subsequently, we conduct a qualitative study aimed at investigating how the identified metadata types can be extracted automatically. [Results and Conclusions] We propose (1) a harmonized conceptual model for the semantic metadata types pertinent to legal requirements analysis, and (2) automated extraction rules for these metadata types based on NLP. We evaluate the extraction rules through a case study. Our results indicate that the rules generate metadata annotations with high accuracy. [less ▲]

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