Lex2KG: Automatic Conversion of Legal Documents to Knowledge Graph

Muhamad Abdurahman, Fariz Darari, Hans Lesmana, Muhtar Hartopo, Immanuel Rhesa, Berty Chrismartin Lumban Tobing

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Legal documents are generally available in the form of PDF which is not machine-readable. A knowledge graph (KG) is a graph describing real-world entities and their relationships, providing structured, machine-readable information. In this paper, we present Lex2KG, a framework for converting legal (PDF) documents into a KG. The legal KG contains various kinds of structured data, such as metadata, document structures, textual content, and relations between legal resources (e.g., amendments and citations). Through Lex2KG, we have successfully converted 784 Indonesian laws into a KG with a total size of over 1.1 million triples. We also present use cases of the legal KG for SPARQL querying, simple chatbots, and legal visualizations, showing how the legal KG generated can be useful in practice.

Original languageEnglish
Title of host publication2021 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665442640
DOIs
Publication statusPublished - 2021
Event13th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021 - Depok, Indonesia
Duration: 23 Oct 202126 Oct 2021

Publication series

Name2021 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021

Conference

Conference13th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021
Country/TerritoryIndonesia
CityDepok
Period23/10/2126/10/21

Keywords

  • Conversion
  • Knowledge Graph
  • Law
  • Legal Documents
  • PDF
  • RDF
  • SPARQL

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