26,979 research outputs found
Recognizing cited facts and principles in legal judgements
In common law jurisdictions, legal professionals cite facts and legal principles from precedent cases to support their arguments before the court for their intended outcome in a current case. This practice stems from the doctrine of stare decisis, where cases that have similar facts should receive similar decisions with respect to the principles. It is essential for legal professionals to identify such facts and principles in precedent cases, though this is a highly time intensive task. In this paper, we present studies that demonstrate that human annotators can achieve reasonable agreement on which sentences in legal judgements contain cited facts and principles (respectively, Îș=0.65 and Îș=0.95 for inter- and intra-annotator agreement). We further demonstrate that it is feasible to automatically annotate sentences containing such legal facts and principles in a supervised machine learning framework based on linguistic features, reporting per category precision and recall figures of between 0.79 and 0.89 for classifying sentences in legal judgements as cited facts, principles or neither using a Bayesian classifier, with an overall Îș of 0.72 with the human-annotated gold standard
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Lexical patterns, features and knowledge resources for coreference resolution in clinical notes
Generation of entity coreference chains provides a means to extract linked narrative events from clinical notes, but despite being a well-researched topic in natural language processing, general- purpose coreference tools perform poorly on clinical texts. This paper presents a knowledge-centric and pattern-based approach to resolving coreference across a wide variety of clinical records comprising discharge summaries, progress notes, pathology, radiology and surgical reports from two corpora (Ontology Development and Information Extraction (ODIE) and i2b2/VA). In addition, a method for generating coreference chains using progressively pruned linked lists is demonstrated that reduces the search space and facilitates evaluation by a number of metrics. Independent evaluation results show an F-measure for each corpus of 79.2% and 87.5%, respectively, which offers performance at least as good as human annotators, greatly increased performance over general- purpose tools, and improvement on previously reported clinical coreference systems. The system uses a number of open-source components that are available to download
Defining International Law Librarianship in an Age of Multiplicity, Knowledge, and Open Access to Law
Many law librarians are experts in international law and legal research. The concept of âinternational law librarianshipâ, however, encompasses something more than a field of study in which a group of experts practise their profession. In the broader sense, the idea suggests a common calling, similar interests, and goals shared by librarians with a range of specialties beyond international law, working in all types of law libraries. What commonalities create and sustain the concept of international law librarianship? This paper suggests that they can be found in: law librariansâ common need to respond to the âmultiplicityâ of information sources facing twenty-first century legal researchers; the development and nurturing of a shared base of professional knowledge; and a common commitment to work toward ensuring free and open access to legal information globally
Towards a Semantic-based Approach for Modeling Regulatory Documents in Building Industry
Regulations in the Building Industry are becoming increasingly complex and
involve more than one technical area. They cover products, components and
project implementation. They also play an important role to ensure the quality
of a building, and to minimize its environmental impact. In this paper, we are
particularly interested in the modeling of the regulatory constraints derived
from the Technical Guides issued by CSTB and used to validate Technical
Assessments. We first describe our approach for modeling regulatory constraints
in the SBVR language, and formalizing them in the SPARQL language. Second, we
describe how we model the processes of compliance checking described in the
CSTB Technical Guides. Third, we show how we implement these processes to
assist industrials in drafting Technical Documents in order to acquire a
Technical Assessment; a compliance report is automatically generated to explain
the compliance or noncompliance of this Technical Documents
Towards a reading of the Vindolanda Stylus Tablets: Engineers and the Papyrologist
We introduce a collaborative project between the Department of Engineering Science and the Centre for the Study of Ancient Documents at the University of Oxford regarding the analysis and reading of the Vindolanda Stylus Tablets. We sketch the imaging and image processing techniques used to digitally capture and analyse the tablets, the development of the image analysis tools to aid papyrologists in the transcription of the texts, and lessons that can be learned so far from such an inter-disciplinary project
Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support
A framework and methodology---termed LogiKEy---for the design and engineering
of ethical reasoners, normative theories and deontic logics is presented. The
overall motivation is the development of suitable means for the control and
governance of intelligent autonomous systems. LogiKEy's unifying formal
framework is based on semantical embeddings of deontic logics, logic
combinations and ethico-legal domain theories in expressive classic
higher-order logic (HOL). This meta-logical approach enables the provision of
powerful tool support in LogiKEy: off-the-shelf theorem provers and model
finders for HOL are assisting the LogiKEy designer of ethical intelligent
agents to flexibly experiment with underlying logics and their combinations,
with ethico-legal domain theories, and with concrete examples---all at the same
time. Continuous improvements of these off-the-shelf provers, without further
ado, leverage the reasoning performance in LogiKEy. Case studies, in which the
LogiKEy framework and methodology has been applied and tested, give evidence
that HOL's undecidability often does not hinder efficient experimentation.Comment: 50 pages; 10 figure
Distributed human computation framework for linked data co-reference resolution
Distributed Human Computation (DHC) is a technique used to solve computational problems by incorporating the collaborative effort of a large number of humans. It is also a solution to AI-complete problems such as natural language processing. The Semantic Web with its root in AI is envisioned to be a decentralised world-wide information space for sharing machine-readable data with minimal integration costs. There are many research problems in the Semantic Web that are considered as AI-complete problems. An example is co-reference resolution, which involves determining whether different URIs refer to the same entity. This is considered to be a significant hurdle to overcome in the realisation of large-scale Semantic Web applications. In this paper, we propose a framework for building a DHC system on top of the Linked Data Cloud to solve various computational problems. To demonstrate the concept, we are focusing on handling the co-reference resolution in the Semantic Web when integrating distributed datasets. The traditional way to solve this problem is to design machine-learning algorithms. However, they are often computationally expensive, error-prone and do not scale. We designed a DHC system named iamResearcher, which solves the scientific publication author identity co-reference problem when integrating distributed bibliographic datasets. In our system, we aggregated 6 million bibliographic data from various publication repositories. Users can sign up to the system to audit and align their own publications, thus solving the co-reference problem in a distributed manner. The aggregated results are published to the Linked Data Cloud
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