Bridging between LegalRuleML and TPTP for Automated Normative Reasoning
(extended version)
- URL: http://arxiv.org/abs/2209.05090v1
- Date: Mon, 12 Sep 2022 08:42:34 GMT
- Title: Bridging between LegalRuleML and TPTP for Automated Normative Reasoning
(extended version)
- Authors: Alexander Steen, David Fuenmayor
- Abstract summary: LegalRuleML is an XML-based representation framework for modeling and exchanging normative rules.
The TPTP input and output formats are general-purpose standards for the interaction with automated reasoning systems.
We provide a bridge between the two communities by defining a logic-pluralistic normative reasoning language based on the TPTP format.
- Score: 77.34726150561087
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: LegalRuleML is a comprehensive XML-based representation framework for
modeling and exchanging normative rules. The TPTP input and output formats, on
the other hand, are general-purpose standards for the interaction with
automated reasoning systems. In this paper we provide a bridge between the two
communities by (i) defining a logic-pluralistic normative reasoning language
based on the TPTP format, (ii) providing a translation scheme between relevant
fragments of LegalRuleML and this language, and (iii) proposing a flexible
architecture for automated normative reasoning based on this translation. We
exemplarily instantiate and demonstrate the approach with three different
normative logics.
Related papers
- Using Large Language Models for the Interpretation of Building Regulations [7.013802453969655]
Large language models (LLMs) can generate logically coherent text and source code responding to user prompts.
This paper evaluates the performance of LLMs in translating building regulations into LegalRuleML in a few-shot learning setup.
arXiv Detail & Related papers (2024-07-26T08:30:47Z) - Normative Requirements Operationalization with Large Language Models [3.456725053685842]
Normative non-functional requirements specify constraints that a system must observe in order to avoid violations of social, legal, ethical, empathetic, and cultural norms.
Recent research has tackled this challenge using a domain-specific language to specify normative requirements.
We propose a complementary approach that uses Large Language Models to extract semantic relationships between abstract representations of system capabilities.
arXiv Detail & Related papers (2024-04-18T17:01:34Z) - Cross-domain Chinese Sentence Pattern Parsing [67.1381983012038]
Sentence Pattern Structure (SPS) parsing is a syntactic analysis method primarily employed in language teaching.
Existing SPSs rely heavily on textbook corpora for training, lacking cross-domain capability.
This paper proposes an innovative approach leveraging large language models (LLMs) within a self-training framework.
arXiv Detail & Related papers (2024-02-26T05:30:48Z) - An Encoding of Abstract Dialectical Frameworks into Higher-Order Logic [57.24311218570012]
This approach allows for the computer-assisted analysis of abstract dialectical frameworks.
Exemplary applications include the formal analysis and verification of meta-theoretical properties.
arXiv Detail & Related papers (2023-12-08T09:32:26Z) - Large Language Models and Explainable Law: a Hybrid Methodology [44.99833362998488]
The paper advocates for LLMs to enhance the accessibility, usage and explainability of rule-based legal systems.
A methodology is developed to explore the potential use of LLMs for translating the explanations produced by rule-based systems.
arXiv Detail & Related papers (2023-11-20T14:47:20Z) - An Ontological Approach to Compliance Verification of the NIS 2 Directive [0.0]
This paper introduces an approach that leverages techniques of semantic representation and reasoning, hence an ontological approach, towards the compliance check with the security measures that textual documents prescribe.
The formalisation of entities and relations from the directive, and the consequent improved structuring with respect to sheer prose is dramatically helpful for any organisation through the hard task of compliance verification.
arXiv Detail & Related papers (2023-06-30T09:10:54Z) - The Whole Truth and Nothing But the Truth: Faithful and Controllable
Dialogue Response Generation with Dataflow Transduction and Constrained
Decoding [65.34601470417967]
We describe a hybrid architecture for dialogue response generation that combines the strengths of neural language modeling and rule-based generation.
Our experiments show that this system outperforms both rule-based and learned approaches in human evaluations of fluency, relevance, and truthfulness.
arXiv Detail & Related papers (2022-09-16T09:00:49Z) - DPCL: a Language Template for Normative Specifications [0.0]
Legal core concepts have been proposed to systematize and relationships relevant to reasoning.
No solution amongst those has achieved general acceptance, and no common ground (representational, computational) has been identified.
This presentation will introduce DPCL, a domain-specific language (norms) for specifying higher-level policies.
arXiv Detail & Related papers (2022-01-12T13:51:11Z) - A Formalisation of Abstract Argumentation in Higher-Order Logic [77.34726150561087]
We present an approach for representing abstract argumentation frameworks based on an encoding into classical higher-order logic.
This provides a uniform framework for computer-assisted assessment of abstract argumentation frameworks using interactive and automated reasoning tools.
arXiv Detail & Related papers (2021-10-18T10:45:59Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.