Modeling and Querying Greek Legislation Using Semantic Web Technologies

Chalkidis, Ilias; Nikolaou, Charalampos; Soursos, Panagiotis; Koubarakis, Manolis

doi:10.1007/978-3-319-58068-5_36

Cited by 24 publications

(20 citation statements)

References 9 publications

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“…In [20], neither the source code of the "Solon" platform nor the set of grammar rules used for legal text parsing are published. On the other hand, while the legal parser presented in [19] is available on Github, it is used to parse documents of the Government Gazette and detect their structure and cannot be used to extract structural elements of court decisions or legal opinions. Moreover, legal references in these documents follow a much stricter drafting style, due to rules set by a special committee, while judges are free to write legal citations according to their personal taste.…”

Section: Discussionmentioning

confidence: 99%

“…Interestingly, during recent years, research teams from Greece have put efforts in parsing Greek legislative documents and transforming them into structured data. Chalkidis et al [19] implemented a rule-based parser that parses PDF documents of the Greek Government Gazette and transforms them into Linked Open Data (RDF triples). In [20] Koniaris et al describe a DSL based approach for parsing legal documents, identifying their structural elements and metadata, and converting plain text to XML following the LegalDocML schema.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

et al. 2019

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Regulation of modern societies requires the generation of large sets of heterogeneous legal documents: bills, acts, decrees, administrative decisions, court decisions, legal opinions, circulars, etc. More and more legal publishing bodies publish these documents online, although usually in formats that are not machine-readable and without following Open Data principles. Until an open by default generation and publication process is employed, ex-post transformation of legal documents into Legal Open Data is required. Since manual transformation is a time-consuming and costly process, automated methods need to be applied. While some research efforts toward the automation of the transformation process exist, the alignment of such approaches with proposed Open Data methodologies in order to promote data exploitation is still an open issue. In this paper, we present a methodology aligned to the Open Data ecosystem approach for the automated transformation of Greek court decisions and legal opinions into Legal Open Data that builds on legal language processing methods and tools. We show that this approach produces Legal Open Data of satisfying quality while highly reducing the need for manual intervention.Information 2020, 11, 10 2 of 30 manual analysis and processing is prohibitive and automated approaches are needed to undertake such tasks [5]. It is noteworthy that some researchers explicitly classify legal documents as Big Data since they meet at least two of the major aspects of Big Data: volume and variety [6]. While several governments are taking steps to apply semantic web technologies in the legal publishing domain (e.g., the legislation.gov.uk platform where UK legislation is published in XML and RDF) [7], in most countries these documents are usually made available in unstructured or poorly structured formats; for example, as PDF files, HTML documents, or plain text.On the other hand, the current trend of Open Data requires that government data (legal documents being a special category of them) are published without technical and legal impediments, in structured and machine-processable formats, and under an open license. Janssen et al. [8] have discussed in detail the expected benefits from the adoption of the Open Data model: transparency, democratic accountability, economic growth, stimulation of innovation, creation of new services, improved decision and policy making, equal access to data, etc. To ensure these benefits of Open Data, researchers propose the "transparency-by-design" model, an organization model for data publication systems, which is expected to contribute to the automatic opening of data [9]. However, this is not yet the case in the legal domain, and the ideal scenario, where legal publishing systems are organized in such a way that legal information is generated in the form of Open Data by default, still seems distant. The availability of data in non-machine-processable formats, and the need for manual processing and conversion are identified as significant barriers for the use of Open Dat...

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

et al. 2019

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“…72 Finlex extends the ELI with the Semantic Finlex Legislation Ontology 73 (SFL) and ECLI with the Semantic Finlex Case Law ontology 74 (SFCL). The greek project Nomothesia (Chalkidis et al 2017) by the University of Athens focuses on legislation only and is based on legal documents published in PDF format which are transformed into linked legal data based on the ELI which is 70 https://seco.cs.aalto.fi/projects/lawlod/. 71 https://data.finlex.fi/.…”

Section: Non-governmental Initiativesmentioning

confidence: 99%

The linked legal data landscape: linking legal data across different countries

2021

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The European Union is working towards harmonizing legislation across Europe, in order to improve cross-border interchange of legal information. This goal is supported for instance via standards such as the European Law Identifier (ELI) and the European Case Law Identifier (ECLI), which provide technical specifications for Web identifiers and suggestions for vocabularies to be used to describe metadata pertaining to legal documents in a machine readable format. Notably, these ECLI and ELI metadata standards adhere to the RDF data format which forms the basis of Linked Data, and therefore have the potential to form a basis for a pan-European legal Knowledge Graph. Unfortunately, to date said specifications have only been partially adopted by EU member states. In this paper we describe a methodology to transform the existing legal information system used in Austria to such a legal knowledge graph covering different steps from modeling national specific aspects, to population, and finally the integration of legal data from other countries through linked data. We demonstrate the usefulness of this approach by exemplifying practical use cases from legal information search, which are not possible in an automated fashion so far.

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“…We use the Person, Organization, and Location annotations only, since the other entity types are not shared across the two datasets. 5 https://commoncrawl.org 6 https://github.com/google-research/bert 7 The Google Cloud TPU v3-8 was provided for free by the TensorFlow Research Cloud (TFRC) program, to which we are grateful. 8 https://github.com/UniversalDependencies/UD_Greek-GDT.…”

Section: Named Entity Recognitionmentioning

confidence: 99%

GREEK-BERT: The Greeks visiting Sesame Street

Koutsikakis

Chalkidis

Malakasiotis

et al. 2020

11th Hellenic Conference on Artificial Intelligence

Self Cite

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Transformer-based language models, such as BERT and its variants, have achieved state-of-the-art performance in several downstream natural language processing (NLP) tasks on generic benchmark datasets (e.g., GLUE, SQUAD, RACE). However, these models have mostly been applied to the resource-rich English language. In this paper, we present GREEK-BERT, a monolingual BERT-based language model for modern Greek. We evaluate its performance in three NLP tasks, i.e., part-of-speech tagging, named entity recognition, and natural language inference, obtaining state-of-the-art performance. Interestingly, in two of the benchmarks GREEK-BERT outperforms two multilingual Transformer-based models (M-BERT, XLM-R), as well as shallower neural baselines operating on pretrained word embeddings, by a large margin (5%-10%). Most importantly, we make both GREEK-BERT and our training code publicly available, along with code illustrating how GREEK-BERT can be fine-tuned for downstream NLP tasks. We expect these resources to boost NLP research and applications for modern Greek.

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Modeling and Querying Greek Legislation Using Semantic Web Technologies

Cited by 24 publications

References 9 publications

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

The linked legal data landscape: linking legal data across different countries

GREEK-BERT: The Greeks visiting Sesame Street

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