This project studied, designed, and evaluated computational methods to support interpretation of statutory terms, and it proposes a novel task of discovering sentences for argumentation about the meaning of statutory terms.
The project modeled the analysis of past treatment of statutory terms, an exercise lawyers routinely perform using a combination of manual and computational approaches. The project treated the discovery of sentences as a special case of ad hoc document retrieval. The specifics include retrieval of short texts (sentences), specialized document types (legal case texts), and, above all, the unique definition of document relevance provided in detailed annotation guidelines. To support the project’s experiments, a data set was assembled composed of 42 queries (26,959 sentences), which the project plans to release to the public soon to support further research. Most importantly, the project investigated the feasibility of developing a system that responds to a query with a list of sentences that mention the term in a way that is useful for understanding and elaborating its meaning. This is accomplished by a systematic assessment of various features that model the sentences’ usefulness for interpretation. Features are combined into a compound measure that accounts for multiple aspects. The definition of the task, the assembly of the data set, and the detailed task analysis provide a solid foundation for employing a learning-to-rank approach. (publisher abstract modified)
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