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Accepting natural language questions makes the system more user-friendly, but harder to implement, as there are a variety of question types and the system will have to identify the correct one in order to give a sensible answer. Assigning a question type to the question is a crucial task; the entire answer extraction process relies on finding ...
Another benchmark dataset is the GeoQuery dataset which contains questions about the geography of the U.S. paired with corresponding Prolog. [27] The Overnight dataset is used to test how well semantic parsers adapt across multiple domains; it contains natural language queries about 8 different domains paired with corresponding λ-DCS ...
In a civil proceeding or criminal prosecution under the common law or under statute, a defendant may raise a defense (or defence) [a] in an effort to avert civil liability or criminal conviction. A defense is put forward by a party to defeat a suit or action brought against the party, and may be based on legal grounds or on factual claims.
In law, an absolute defence (or defense) is a factual circumstance or argument that, if proven, will end the litigation in favor of the defendant. [1] The concept of an absolute defence is not a rigid one. Statutes frequently use the term merely as a synonym to "full" or "complete".
In the common law, an answer is the first pleading by a defendant, usually filed and served upon the plaintiff within a certain strict time limit after a civil complaint or criminal information or indictment has been served upon the defendant.
The Stanford team claims their questions are a better test of how legal copilots may perform in a real-world setting than bar exam questions—especially because a lot of datasets of bar exam ...
Accurate legal information retrieval is important to provide access to the law to laymen and legal professionals. Its importance has increased because of the vast and quickly increasing amount of legal documents available through electronic means. [2] Legal information retrieval is a part of the growing field of legal informatics.
The former is based on the use of datasets designed by experts and composed of word pairs with semantic similarity / relatedness degree estimation. The second way is based on the integration of the measures inside specific applications such as information retrieval, recommender systems, natural language processing, etc.