This paper proposes several recurrent neural network-based models for recognizing requisite and effectuation parts in Legal Texts. Firstly, we propose a modification of BiLSTM-CRF model that allows the use of external features to improve the performance of deep learning models in case large annotated corpora are not available. However, this model can only recognize RE parts which are not overlapped. Secondly, we propose two approaches for recognizing overlapping RE parts including the cascading approach which uses the sequence of BiLSTM-CRF models (...) and the unified model approach with the multilayer BiLSTM-CRF model and the multilayer BiLSTM-MLP-CRF model. Experimental results on two Japan law RRE datasets demonstrated advantages of our proposed models. For the Japanese National Pension Law dataset, our approaches obtained an \ score of 93.27% and exhibited a significant improvement compared to previous approaches. For the Japan Civil Code RRE dataset which is written in English, our approaches produced an \ score of 78.24% in recognizing RE parts that exhibited a significant improvement over strong baselines. In addition, using external features and in-domain pre-trained word embeddings also improved the performance of RRE systems. (shrink)

We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep neural networks. On the other hand, we explore the benefits from combining lexical features and latent features generated with neural networks. Our experiments show that lexical features and latent features generated with neural networks complement each other to improve the retrieval system performance. Furthermore, our experimental results suggest the (...) importance of case summarization in different aspects: using provided summaries and performing encoded summarization. Our approach achieved F1 of 65.6% and 57.6% on the experimental datasets of legal case retrieval tasks. (shrink)

Artificial agents, which are embedded in a virtual world, need to interpret a sequence of commands given to them adequately, considering the temporal structure for each command. In this paper, we start with the semantics of natural language and classify the temporal structures of various eventualities into such aspectual classes as action, process, and event. In order to formalize these temporal structures, we adopt Arrow Logic. This logic specifies the domain for the valuation of a sentence as an arrow. We (...) can connect, or give order to, arrows by defining inter-arrow operations, and can give different views for sentences. Thereafter we formalize the rules of aspectual shifts in situated inference, in the style of a logic programming language. Thus, we not only describe the static representation of temporal features, but also show the dynamic process to deduce how each eventuality is viewed. The rules are applied to the information flow through the sequence of commands; therefore, we consider how the temporal structure of a command affects the succeeding commands. (shrink)

In one of his papers, JC Beall advanced a new and interesting interpretation of Weak Kleene logic, in terms of on-topic/off-topic. In brief, Beall suggests to read the third value as off-topic, whereas the two classical values are read as true and on-topic and false and on-topic. Building on Beall’s new interpretation, the aim of this paper is threefold. First, we discuss two motivations to enrich Beall’s interpretation, and offer an alternative semantic framework that reflects our motivations. Second, by making (...) use of our new framework, we will offer a new interpretation of the logic of Catuskoti which combines Beall’s proposal of having FDE as the correct logic with the on-topic/off-topic divide. Finally, we will offer a general result that will allow us to make sense of a family of infectious logics in terms of Beall’s on-topic/off-topic reading. (shrink)

This study realizes belief/reliability change of a judge in a legal judgment by dynamic epistemic logic. A key feature of DEL is that possibilities in an agent’s belief can be represented by a Kripke model. This study addresses two difficulties in applying DEL to a legal case. First, since there are several methods for constructing a Kripke model, our question is how we can construct the model from a legal case. Second, since this study employs several dynamic operators, our question (...) is how we can decide which operators are to be applied for belief/reliability change of a judge. In order to solve these difficulties, we have implemented a computer system which provides two functions. First, the system can generate a Kripke model from a legal case. Second, the system provides an inconsistency solving algorithm which can automatically perform several operations in order to reduce the effort needed to decide which operators are to be applied. By our implementation, the above questions can be adequately solved. With our analysis method, six legal cases are analyzed to demonstrate our implementation. (shrink)

Case-based reasoning has played an important role in legal reasoning systems. As one criteria for similarity of cases, temporal relationsamong affairs in legal cases should be compared. Thus far in many legalreasoning systems, cases have been described as sequences of pointwiseevents, or at best, simple time intervals, and they have been related bypredicates such as before, after, while,and so on. However, such relations may depend on each implementer'spersonal view, and also require much labor to write down by hand. In this (...) paper, we first propose a classification of affair types by their temporal features, and according to those types, we propose several assumption rules that prescribe the temporal relations between affair types. The temporal relations are automatically generated by these rules. Thereafter, we discuss how thesetemporal relations work in the comparison of similarity of cases. Inthe process of comparison, inadequate temporal relations need to beamended. For this purpose, we introduce revision rules, that refute theresults of assumption rules. (shrink)