We present a framework for deriving inference relations between Dutch sentence pairs. The proposed framework relies on logic-based reasoning to produce inspectable proofs leading up to inference labels; its judgements are therefore transparent and formally verifiable. At its core, the system is powered by two ${\lambda}$-calculi, used as syntactic and semantic theories, respectively. Sentences are first converted to syntactic proofs and terms of the linear ${\lambda}$-calculus using a choice of two parsers: an Alpino-based pipeline, and Neural Proof Nets. The syntactic terms are then converted to semantic terms of the simply typed ${\lambda}$-calculus, via a set of hand designed type- and term-level transformations. Pairs of semantic terms are then fed to an automated theorem prover for natural logic which reasons with them while using the lexical relations found in the Open Dutch WordNet. We evaluate the reasoning pipeline on the recently created Dutch natural language inference dataset, and achieve promising results, remaining only within a $1.1-3.2{\%}$ performance margin to strong neural baselines. To the best of our knowledge, the reasoning pipeline is the first logic-based system for Dutch.
翻译:我们提出了一个荷兰判决对配方之间推断关系的框架。 拟议的框架依赖基于逻辑的推理来提出可检验的证据,导致推断标签; 因此,其判断是透明和正式可核查的。 在其核心, 系统由2美元( lambda) $- calculi 驱动, 分别用作合成和语义理论。 判决首先转换成以线性证据和线性 $( lambda) 计算术语术语的合成证据和术语。 使用两种分析器的选择: 以阿尔卑诺为基础的管道, 和 Neural Subence Nets 。 合成术语随后被转换成简单的打入 $( lambda) $( $) 的语义术语的语义术语。 通过一套手工设计的型和语义级变变和语义理论。 语义术语的音调随后被转换成一个自动的词义验证逻辑, 与自然逻辑的关系在荷兰公开 WordNet 中发现。 我们只评估最近创建的荷兰自然语言的逻辑的逻辑术语的推理学术语, 也就是我们最强的逻辑的逻辑的逻辑推理, 的逻辑推算, 至最精确的逻辑的逻辑推算。