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Decoding Legal Speak: A Laymans Guide To Legal Ontologies And Knowledge Graphs

SUMMARY: The blog explores the link between Ontologies and Legal Knowledge Graphs, highlighting their potential for facilitating ‘explainable AI’ in the legal system, ensuring fairness, and transparency in AI adoption.

Key takeaways

  1. Crucial Role of Ontologies: Ontologies serve as essential frameworks in AI, acting as blueprints for legal knowledge, defining terms, relationships, and rules.
  2. Improved Legal Research: The convergence of Legal Ontologies and (Knowledge Graphs) KGs streamlines legal processes, providing user-friendly guides for navigating through legal landscapes, and fostering a more effective and precise legal research experience.
  3. India’s Need for Legal Knowledge Graphs: In a pluralistic society like India, Legal Knowledge Graphs can modernize the legal system, offering a standardized framework for interpretation, fostering fairness, and enhancing transparency tailored to the unique intricacies of the Indian legal landscape.


In the realm of Artificial Intelligence (AI), ontologies stand as crucial frameworks for knowledge representation. Much like the index of a book, ontologies provide a structured map for understanding entities and their relationships within a specific domain. Many consider ‘Ontology’ as the missing link between legal theory and ‘AI and Law’.            In this piece, we delve into:

  • the relationship between Ontologies and Legal Knowledge Graphs (LKGs);and
  • how (if used properly) they could help in the adoption of ‘explainable AI’ in the Legal system – a mechanism that can ensure fairness and transparency while adopting AI into the legal system.

Legal Ontology serves as the conceptualisation of the building blocks of legal knowledge. Think of it as the architect’s blueprint, providing a structured representation of legal concepts, relationships, and rules. Each defined term becomes a crucial building block, akin to a piece of a puzzle that contributes to the overall picture of the legal landscape.

Knowledge Graphs (KGs) then step in as the dynamic networks connecting these building blocks, illustrating the convoluted relationships amongst legal concepts, much like the interplay between various elements in a complex structure. An LKG can, therefore, be defined as a “graph of legal data intended to accumulate and convey knowledge of law, whose nodes represent entities of interest and whose edges represent relations between these entities.”

To simplify, picture legal ontology as the blueprint and KGs as the interactive 3D model, offering a visual guide to how these building blocks fit together. These tools facilitate not only legal professionals but also laymen in understanding the intricacies of the law by organising information in a clear and structured manner.

Figure 1


Convergence of Legal Ontologies and KGs – Provides for better understanding of legal system

Navigating legal processes often feels like manoeuvring through a labyrinth of paperwork and jargon. Legal ontologies (which precisely define each term) and KGs (which visually map relationships amongst these terms) can act as user-friendly guides, breaking down complex legal concepts into digestible pieces. Let’s consider a common scenario – searching for legal information online. The legal ontologies and KG tools can transform the process into an intuitive search experience, akin to using a search engine tailored specifically for legal queries. Legal ontologies provide precise definitions for each legal term, and KGs illustrate the relationships between these terms. This simplification not only improves understanding but also empowers individuals to engage more effectively with legal documents. Users, from seasoned lawyers to common man, can effortlessly navigate through legal landscapes, finding relevant information with unprecedented ease.

Interoperability and Democratising the legal discourse

Moreover, legal ontologies and KGs address a persistent problem in legal research – the inconsistency in the usage of terms across hierarchical courts or courts in different states, despite identical meanings. In traditional search scenarios, this variation can result in inefficiencies and confuse common men and even legal practitioners. However, the integration of ontologies and KGs offers a transformative solution. With this integration, users gain the ability to navigate seamlessly through different jurisdictions, gaining a comprehensive understanding of how terms are utilized in diverse legal contexts. This functionality not only streamlines the research process but also ensures a more accurate and thorough comprehension of legal concepts. Regardless of geographical or hierarchical nuances, the use of ontologies and KGs empowers legal professionals and common men to navigate the intricacies of the legal landscape with clarity and efficiency, fostering a more effective and precise legal research experience. In other words, this initiative will go a long way in democratising the legal profession.

Large Language Models and KGs – Improving the quality of performance of Generative AI

In the era of Chat GPT and generative AI, the ubiquity of Large Language Models (LLMs) is difficult to ignore. LLMs and LKGs are complementary technologies that balance each other’s strengths and weaknesses when combined. For example, LLMs have a strong capability for understanding and generating natural language, but can sometimes hallucinate facts while LKGs explicitly represent factual knowledge in a structured format, but lack understanding of language. When combined together, LLMs can provide context and nuance to the rigid facts in KGs, while KGs can ground the free-flowing text from LLMs in reality.

Additionally, legal ontologies contribute to transparency by precisely defining legal terms and illuminating the relationships amongst legal concepts through KGs. These interconnected networks provide a visual representation of how various legal elements relate to one another. This transparency not only aids in understanding the intricate web of legal concepts but also allows for the identification and correction of any potential biases embedded in the system. As a result, these tools can ensure:

  • the functioning of generative AI models with a reasonable degree of accuracy;
  • the development of advanced legal analytics, allowing for the analysis of vast legal datasets; and
  • creation of a more equitable legal environment.


Relevance of LKG in a pluralistic society

India – the abode of highly pluralistic society, stands at the forefront of the need for a KG in the legal domain. Building such a system would not only streamline and modernise the Indian legal system but also provide a standardised framework for interpretation, fostering fairness, and enhancing transparency. Moreover, these tools can pave the way for the development of advanced legal tech solutions tailored to the unique intricacies of the Indian legal landscape.

In the dynamic synergy of law and AI, legal ontologies and KGs emerge as indispensable tools. While simplifying legal processes, enhancing accessibility, and promoting fairness and transparency, these tools also address the inherent challenges of accommodating diverse legal systems and providing for explainability in the decision-making process. As we navigate through the intricacies of the law, the creation of a legal knowledge representation becomes crucial for building maintainable and scalable models. Legal ontologies and KGs not only conceptualise the building blocks of legal knowledge but also contribute to the operational legal knowledge systems that are shaping the future of law.

Democratisation of legal discourse

The synergy between advanced technologies, such as Chat GPT and LKGs, could redefine the landscape of legal services, making them more accessible, transparent, and user-friendly. A cutting-edge virtual assistant, powered by LKGs, could guide individuals through sophisticated legal procedures, offering real-time insights and tailored advice. This not only democratizes access to legal information but also empowers individuals to make informed decisions. In essence, the marriage of legal ontologies and KGs is not merely an evolution; it is a game-changer, revolutionizing how we engage with the intricate world of law.


  1. André Valente and Joost Breuker, ‘Ontologies: The Missing Link Between Legal Theory and AI &Law’ in H Prakken, A Muntjewerff and A Soeteman (eds),  Legal Knowledge Based Systems (Jurix 1994).
  2. Explainable AI(XAI) is “artificial intelligence (AI) that’s programmed to describe its purpose, rationale and decision-making process in a way that can be understood by the average person. XAI helps human users understand the reasoning behind AI and Machine Learning (ML) algorithms to increase their trust.” Alexander Gillis, ‘explainable AI (XAI)’ (TechTarget) <www.techtarget.com/whatis/definition/explainable-AI-XAI>accessed 2 February 2024
  3. Aidan Hogan and others, Knowledge Graphs (Synthesis Lectures on Data, Semantics, and Knowledge Series, Springer 2022).
  4. Anjaneya Tripathi, ‘Knowledge_Graph’ (GitHub) <https://github.com/AnjaneyaTripathi/knowledge_graph/blob/master/results/images/revamped_kg10.png> accessed 3 February 2024.

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