Information extraction for legal knowledge representation – a review of approaches and trends <s> IR Systems based on keyword indexing <s> Normative texts can be viewed as composed by formal partitions (articles, paragraphs, etc.) or by semantic units containing fragments of a regulation (provisions). Provisions can be described according to a metadata scheme which consists of provision types and their arguments. This semantic annotation of a normative text can make the retrieval of norms easier. The detection and description of the provisions according to the established metadata scheme is an analytic intellectual activity aiming at classifying portions of a normative text into provision types and to extract their arguments. Automatic facilities supporting this intellectual activity are desirable. Particularly, in this paper, two modules able to qualify fragments of a normative text in terms of provision types and to extract their arguments are presented. <s> BIB001 </s> Information extraction for legal knowledge representation – a review of approaches and trends <s> IR Systems based on keyword indexing <s> One of the main emerging research challenge in the legal documentation is to penetrate in the meaningful and in the semantic of the norm content using NLP techniques and isolate relevant part of the linguistic speech. This paper wants present a methodology for modeling the modificatory provisions in deep in order to provide all the necessary formalization for managing semi-automatically the consolidation process. <s> BIB002
With the objective of reviewing concepts in this field, the classical IR approach is briefly described. This approach can be found in the first IR systems developed and its analysis provides important indications of its limitations. The term "Information Retrieval" usually indicates the manipulation and organization of textual data, although, in a broader sense, it can also specifies the retrieval of records composed by different kinds of data. This is particularly true in Internet context, since the current technological infrastructure provides the access to a great amount of different kinds of data, such as images, audio, video, sensor data or structured data  Particularly for the legal domain, it is important the treatment of textual and structured data records. The first one is available in repository of documents and is composed mainly by free-form natural language text, given some formalism and textual structure observed in legal area. The second one is available in recent but increasingly available digital repositories that are mainly related to e-government initiatives BIB002 BIB001 17] . Considering some collection of documents related to a specific knowledge field, the typical IR system should provide a mechanism that responds to information necessities formulated by a user or by a system, in an efficient and accurate way. The information needs are expressed in queries that can be more general or more specific. It is also possible that the queries can be accomplished by a great number of documents in the collection, which should be treated by the IR system in a process called ranking. A classic example of architecture for IR systems based on word indexing can be seen in Figure 1 . Initially, the system components deal with documents and user needs. The documents are used in an indexing process that generates index sets and documents representations, describing document relevant features for the next processing step, such as features to ranking generation. The index sets and the document representation are both used along with the query specification in the recovery process. At the end of this process, the system retrieves a list of documents considered to be relevant   . The models typically observed in classical IR process are the Boolean, Vector and Probabilistic 17. In general, document search strategies are relevant to a given kind query and necessity. These models assume that each document is described by a set of keywords, called indexing terms. Each indexing term in a document has a weight that quantifies the correlation between the term and the document. This correlation is used to calculate the relevance of the document to the query. The keyword indexing approach is commonly used for the implementation of search systems, and in legal domain some IR systems are implemented based on this approach. Some of those are commented in the next section.