Automated Semantic Annotation Pipeline for Brazilian Judicial Decisions

Legal experts can reliably ascertain which legal norms are valid, and therefore which legal propositions are true. Legal experts are in this position because they have a grasp of the deep cognitive structure of law: the habits, commitments, and values that characterize the practice of legal argument in a specific jurisdiction. Legal expertise, thus understood, determines the content of the law, which is therefore not reducible to an aggregation of authoritative legal texts. Because social facts about legal experts’ values and commitments can determine the content of the law, references to moral considerations and principles of justice as valid legal reasons, in legal argument, are not a problem for (at least some forms of) legal positivism. Legal expertise thus shows that non-positivists might be right about (as they would put it) the irreducibility of legal content to communicative content without being right about the claims that moral facts determine the content of the law or that the validity of legal norms turns on moral considerations. Legal expertise also plays an important causal role in legal decision-making and is not, as some of the literature on judicial decision-making might suggest, epiphenomenal. From a moral perspective, while the existence of a class of legal experts is not necessarily valuable, it does have certain benefits, particularly in conditions of moral disagreement.

Due to the heavy workload of RSS collection, the instability of WLAN signal strength and the disappearance of signals caused by complex indoor environments, the construction of radio map for wireless local area network (WLAN) fingerprint-based indoor positioning system is time-consuming and laborious. In order to rapidly deploy indoor WLAN positioning system, the bidirectional encoder representation from transformers (BERT) model is used to fill the missing signal in radio map and quickly build radio map. The radio map is imported into the BERT model in the form of natural language text, and the missing signal is filled by the BERT model. Since the number of input data in BERT model cannot exceed 512 words, the structure of BERT model is not suitable for WLAN signals with large data volume. Therefore, we redefine the model structure based on the original BERT model and fill in the missing signals in the radio map in parallel. In addition, the loss function is redefined. Except that each segment has a loss function, the weighted average value of all segment loss functions is defined as the total loss function. The experimental results show that the BERT model is better than the traditional linear interpolation method, compressed sensing algorithm and matrix completion algorithm in filling the missing signals in the fingerprint database, and the probability of error within 2 m reaches about 94%.

Background: Web documents display information in the form of natural language text which is not understandable by machines. To search specific information from sea of web documents has become very challenging as it shows many unwanted non relevant documents along with relevant documents. To retrieve relevant information semantic knowledge can be stored in the domain specific ontology which helps in understanding user’s need to retrieve relevant information. Methods: In this paper, framework for extracting and visualising semantic knowledge has been designed. Proposed approach is based on the assumption that semantics of text can be extracted by creating syntactic structure of the text. To extracts syntactic structure Stanford parser has been used. Parsing of corpus text is done to obtain morphological structures which is in more machine readable format, and thus provides a better structure for constructing syntactic-semantic rules manually. The tagged form of each sentence is taken and set of rules based on dependency relationship are build manually. Sentence level analysis is performed for concepts generation, for properties and for hierarchical relation extraction using dependency parse tree as a means for relation extraction. Results: Extracted concepts and relation among various entities constitute knowledge base in the form of ontology. Conclusion: Proposed information extraction model successfully filter the desired information from the large ocean of internet and create semantic structure to represent data in standard machine understandable format which explain the details about entities along with their properties and their relationship.

The paper is devoted to the development and implementation of effective models of medical data classification by text mining for decision support in the diagnosis of pulmonological diseases in children and adolescents of the Altai Territory. Medical data contains important information about patients. Test results are usually retained as structured data, but some data are retained in the form of natural language texts (medical history, the results of physical examination, and the results of other examinations). The paper assesses the quality of the developed methods for extracting information from clinical texts. An assessment of the method for the automatic diagnosis of pulmonological diseases in a test sample is conducted. The most informative features, as well as suitable machine learning methods for classifying patients by disease groups, are identified. Many tasks arising in clinical practice can be automated by applying methods for intelligent analysis of structured and unstructured data that will lead to improvement of the healthcare quality. The results of the research indicate the prospect of using models to support decisionmaking in the primary diagnosis of pulmonological diseases in children and adolescents of the Altai Territory.

Informal discussions on social platforms (e.g., Stack Overflow, CodeProject) have accumulated a large body of programming knowledge in the form of natural language text. Natural language process (NLP) techniques can be utilized to harvest this knowledge base for software engineering tasks. However, consistent vocabulary for a concept is essential to make an effective use of these NLP techniques. Unfortunately, the same concepts are often intentionally or accidentally mentioned in many different morphological forms (such as abbreviations, synonyms and misspellings) in informal discussions. Existing techniques to deal with such morphological forms are either designed for general English or mainly resort to domain-specific lexical rules. A thesaurus, which contains software-specific terms and commonly-used morphological forms, is desirable to perform normalization for software engineering text. However, constructing this thesaurus in a manual way is a challenge task. In this paper, we propose an automatic unsupervised approach to build such a thesaurus. In particular, we first identify software-specific terms by utilizing a software-specific corpus (e.g., Stack Overflow) and a general corpus (e.g., Wikipedia). Then we infer morphological forms of software-specific terms by combining distributed word semantics, domain-specific lexical rules and transformations. Finally, we perform graph analysis on morphological relations. We evaluate the coverage and accuracy of our constructed thesaurus against community-cumulated lists of software-specific terms, abbreviations and synonyms. We also manually examine the correctness of the identified abbreviations and synonyms in our thesaurus. We demonstrate the usefulness of our constructed thesaurus by developing three applications and also verify the generality of our approach in constructing thesauruses from data sources in other domains.

The analysis of the norms of the Criminal Code of Ukraine allowed to establish the availability of only two articles (Articles 343, 386) that provide responsibility for illegal actions against an expert. It has been stated that among the victims of such criminal offenses, the theory of law defines exactly judicial experts. In the article, an attempt is made to investigate the question of whether legal experts belong to the category of judicial specialists (experts), and to evaluate the legal significance of the scientific and legal conclusions they prepare. It was affirmed that the relevant legislation does not provide the recognition by a judicial expert of such a specialist as an expert on legal issues. It has been established that certain procedural (civil, economic and administrative justice) codes divide the categories of legal expert” and “judicial expert”, which are significantly different; however, the criminal procedural code of Ukraine does not contain such a concept at all, but uses the term expert as a participant in the criminal process, that is a judicial expert. The analysis of judicial practice and scientific literature allowed us to assume that the conclusions of scientific and legal expertise are used in the criminal process. It has been proven that the Supreme Court and the Constitutional Court of Ukraine use in their practice the conclusions of the members of the scientific advisory councils, i.e. experts in the field of law. A certain injustice was noted regarding the possibilityof using conclusions on legal issues in court proceedings at different levelsof the judicial system. The considered provisions of the regulatory legal acts allowed to classify expert conclusions on legal issues depending on certain criteria: by legal meaning (prohibited for use and permitted for use); by compensatory nature (paid and unpaid); according to the procedure of involving an expert (on the initiative of the participants in the process and on the initiative of the court). The article suggests the characteristics of an expert conclusion on legal issues: it has a recommendatory character; has local legal significance (refers to a specific court case); is not evidence in the case; does not entail legal responsibility for the expert; can be prepared by both an individual and a legal entity. The conducted research allowed to draw certain conclusions: a legal specialist (expert) does not belong to the category of judicial experts; the legal status of a legal specialist (expert) and a judicial expert have significant differences; the victim in the commission of criminal offenses provided in Articles 343 and 386 of the Criminal Code of Ukraine cannot be a legal specialist (expert); based on the study of foreign experience, law-making activity, current legislation and national law enforcement practice, it is proposed to extend such a legal institution to the Criminal Procedure Code of Ukraine and the Code of Ukraine on Administrative Offenses; in the legislation, it is recommended to provide a mechanism of criminal legal protection of the activity of a legal specialist (expert) by making appropriate changes to Articles 343 and 386 of the Criminal Code of Ukraine.

Semantic annotation approaches link entities from a knowledge base to mentions of entities in text to provide additional content-related information. Recently increasing use of resources from the Linked Open Data (LOD) Cloud has been made to annotate text documents thanks to the network of machine-understandable, interlinked data. While existing approaches to semantic annotation in the LOD context have been proven to be well performing with the English language, many other languages in general and the Korean language in particular are still underrepresented. We investigate the applicability of existing semantic annotation approaches to the Korean language by adapting two popular approaches in the semantic annotation field and evaluating those approaches on an English-Korean bilingual sense-tagged corpus. Further, general challenges in internationalization of annotation approaches are summarized.

The regulations over civil marriage in post-unification Italy envisioned the possibility of annulling a union for reasons of sexual impotence of one of the spouses. This article examines a series of judicial proceedings for annulment on grounds of male impotence and, in particular, the medical -legal expertise that was adduced over the course of a case. The sexual incapacity of a husband and its consequences reveal how the body was conceptualized through a dense nexus between subjectivity, family ties, and social norms. In addition, the difficulties inherent in the medial -legal trial raise the problem of the relationship between doctors and jurist in the tribunal and, above all, enable us to investigate the change that the growing influence of psychiatrists played in the outcome of cases.

Semantic annotation refers to the process of annotating documents using the ontology in order to data becomes meaningful. Most of the techniques and methods of the field of semantic annotation and retrieval are used for dealing broadly in the English language. This paper aims to enhance the process of information retrieval for Arabic language that depends on the ontology in the process of document annotation. To achieve this aim, it is determined and processed the problems of the Arabic language through the proposed approach. This paper depends on semantic annotation based on ontology and Resource Description Framework (RDF). The results achieved high precision and high recall for the semantic annotation based on the proposed approach.

Social studies on the communication problems between the state, society, and citizens are particularly relevant in the modern world. This article is dedicated to a way of enhancing the quality of communication between lawmakers and society known as "normative promotion." The author proposes to understand normative promotion as the activities of a regulator (lawmaker) aimed at forming a unified communicative legal space by informing citizens (the addressees of legal regulation in general) about the legal regulation being introduced, explaining the content of new legal acts or legal norms with the aim of fostering a conscious attitude towards these norms and a positive perception of legal regulation. Ignoring the systematic work of the state in the field of normative promotion can lead to both a decrease in the effectiveness of regulation in general and the emergence of social tension and conflicts within society in particular. It is advisable to consider the practices of normative promotion from the perspective of the communicative theory of law, which serves as the methodological basis for the research, namely, in the context of the dialogue between the legislator and society, where the main role is played not by the regulator as the author of the message, but by the addressee, that is, society or citizens. By examining the connection between normative promotion and other methods of enhancing the quality of lawmaking communication, the author addresses the question of whether the practice of normative promotion has practical significance for legal expertise as an activity aimed at assessing the quality of legal acts. As a result, the author concludes that organizational means, such as deliberative practices, legal expertise, and normative promotion, can serve to improve communication. The article also argues that the improvement of communication should be ensured by legal means, as all the aforementioned practices are poorly or not at all legally supported. In particular, normative promotion, as an activity related to shaping public opinion, is associated with risks of abuses and political manipulations, thus requiring strict legal regulation. Furthermore, it is justified that technical means, primarily information technologies, should also contribute to improving communication between lawmakers and society, which can be applied in parliamentary activities, particularly in ensuring dialogue between parliamentarians and citizens, normative crowdsourcing, legal information dissemination, and legal (including public) expertise of draft legal acts.

This article discusses how legal professionals perceive the change in their work practices and work-related boundaries as they participate in the design and implementation of a new information system. By looking empirically at a large-scale IT development project within the judicial system in Finland, the paper contributes to debates on how technology development affects the key elements of legal work and how legal expertise is perceived when designing IT systems for the public judiciary. Drawing from research literature on science and technology studies (STS), particularly literature on expertise and boundaries, the article suggests four main findings. First, IT design is seen as an additional task with clear boundaries between legal and technological knowledge. Second, the embodied aspects of legal expertise are connected to issues of autonomy and individual work practices. Third, IT design and use affect organizational flexibility and boundaries between and within organizations. Fourth, there are changes in hierarchical relations and work divisions between judges and legal secretaries.

Europe's vision is to establish a well-functioning Digital Single Market, where Europeans are able to move and trade among the EU member states. On the other hand the large amount of information about laws that apply in each EU country has posed significant barriers in this vision. Moreover only legal experts can follow the latest legislation in each country consuming a large amount of business resources in order to follow the current legislation. However, Mass customization tools can help to filter and thereby reduce the flood of legal information and make it easier to be followed from businesses and citizens without legal expertise. The proposed solution is a novel ICT architecture utilising and built upon text mining, advanced processing and semantic analysis of legal information towards the provision of a set of services for citizens, businesses, and administrations of the European Union. In order to provide the most appealing, comprehensive and added value services in the legal domain, this paper presents six use case scenarios based on the opinion of different target groups. Conducting interviews and focus groups, we were able to identify the novel functionalities and services of great importance for the users highlighting and addressing users' daily problems regarding legal information. Generally, interviews with the different target groups reveal that at this point, users prioritise their needs towards more basic services such as search functionalities and correlation with previous laws. Lawyers on the other hand as more competent target group asked for summarisation and reporting services. All target groups where eager on the implementation of this service which as it seems it will directly impact their everyday professional and personal use of legal information.

The article addresses the imperative of ensuring consistency in legal application through the mandatory legal conclusions of the Supreme Court of Ukraine, a significant aspect in light of ongoing judicial reform. The introductory section highlights the importance of judicial practice stability as a cornerstone of legal certainty and the rule of law in a democratic state. The author examines the Supreme Court’s enhanced role following the 2016 amendments to the Constitution and the Law on the Judiciary and the Status of Judges, which positioned the Supreme Court as the sole cassation instance. This has allowed the Supreme Court to establish binding legal conclusions for lower courts, aiding in the elimination of legal inconsistencies and fostering predictability in judicial decisions. In addition to legal aspects, the article explores theoretical and practical challenges associated with the binding nature of legal conclusions. The author notes the advantages of a unified approach in legal application while also addressing potential risks to judicial independence, which could limit judges’ ability to interpret the law according to the case’s unique circumstances. An important facet is the comparative analysis of other countries’ experiences in ensuring uniform judicial practice, such as precedent-based decisions in the United Kingdom or normative interpretation in continental law systems. Ukraine is striving to identify an optimal approach that achieves legal certainty while allowing flexibility in judicial practice. Through the research, the author proposes ways to improve the legislative regulation of binding legal conclusions by analyzing their impact on judicial practice and drawing on the experience of European nations. The benefits and drawbacks of mandatory legal conclusions are discussed, particularly their role in reinforcing legal order and ensuring equality before the law. The analysis also includes mechanisms allowing the Supreme Court to adjust its legal positions in response to new circumstances, enhancing the legal system’s efficiency and public trust in justice. The article concludes with recommendations emphasizing the need for unity in legal application as the foundation for legal system stability and the further enhancement of institutional independence within the judiciary to uphold fair justice.

PurposeThree-dimensional computer-aided design (CAD) assembly model has become important resource for design reuse in enterprises, which implicates plenty of design intent, assembly intent, design experience knowledge and functional structures. To acquire quickly CAD assembly models associated with specific functions by using product function requirement information in the product conceptual design phase for model reuse, this paper aims to find an approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model before functional semantic-based assembly retrieval.Design/methodology/approachAn approach for structure-function correlations analysis and functional semantic annotation of CAD assembly model is proposed. First, the product knowledge model is constructed based on ontology including design knowledge and function knowledge. Then, CAD assembly model is represented by part attributed adjacency graph and partitioned into multiple functional regions. Assembly region and flow-activity region are defined for structure-function correlations analysis of CAD assembly model. Meanwhile, the extraction process of assembly region and flow-activity region is given in detail. Furthermore, structure-function correlations analysis and functional semantic annotation are achieved by considering comprehensively assembly structure and assembled part shape structure in CAD assembly model. After that, a structure-function relation model is established based on polychromatic sets for expressing explicitly and formally relationships between functional structures, assembled parts and functional semantics.FindingsThe correlation between structure and function is analyzed effectively, and functional semantics corresponding to structures in CAD assembly model are labeled. Additionally, the relationships between functional structures, assembled parts and functional semantics can be described explicitly and formally.Practical implicationsThe approach can be used to help designers accomplish functional semantic annotation of CAD assembly models in model repository, which provides support for functional semantic-based CAD assembly retrieval in the product conceptual design phase. These assembly models can be reused for product structure design and assembly process design.Originality/valueThe paper proposes a novel approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model. Functional structures in assembly model are extracted and analyzed from the point of view of assembly structure and function part structure. Furthermore, the correlation relation between structures, assembled parts and functional semantics is expressed explicitly and formally based on polychromatic sets.

The advancement of artificial intelligence (AI) technology has brought significant transformations across various sectors, including the judicial system. Countries such as China and the United States have adopted AI in legal decision-making, whereas Indonesia remains in the early stages of implementing this technology. While AI has the potential to enhance judicial efficiency, challenges related to regulation, transparency, and algorithmic bias raise concerns regarding the accuracy and fairness of legal rulings. Therefore, this study aims to analyze the effectiveness of AI utilization in Indonesia’s judicial system, identify key challenges, and propose policy recommendations. This research employs both normative and empirical approaches by examining AI-related regulations and conducting interviews with judges and technology experts in Indonesia. The findings indicate that 65% of judges in Indonesia remain skeptical about AI's role in legal decision-making. In contrast, in countries like China, AI adoption in the judiciary has improved case resolution efficiency by 30–40%. Additionally, a public survey reveals that while 55% of respondents believe AI can enhance the objectivity of legal rulings, 45% remain concerned about potential algorithmic bias. Furthermore, the study highlights that Indonesia lacks specific regulations governing AI in the legal system, which may hinder the widespread adoption of this technology. This research contributes to understanding the readiness of Indonesia’s judicial system in integrating AI and emphasizes the necessity of clear regulations and robust oversight mechanisms to ensure transparency and accountability. The findings are expected to serve as a foundation for policymakers in formulating comprehensive regulations to optimize AI implementation in the Indonesian judicial system