Parsing as Deduction Revisited: Using an Automatic Theorem Prover to Solve an SMT Model of a Minimalist Parser

Sagar Indurkhya
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引用次数: 1

Abstract

We introduce a constraint-based parser for Minimalist Grammars (MG), implemented as a working computer program, that falls within the long established “Parsing as Deduction” framework. The parser takes as input an MG lexicon and a (partially specified) pairing of sound with meaning - i.e. a word sequence paired with a semantic representation - and, using an axiomatized logic, declaratively deduces syntactic derivations (i.e. parse trees) that comport with the specified interface conditions. The parser is built on the first axiomatization of MGs to use Satisfiability Modulo Theories (SMT), encoding in a constraint-based way the principles of minimalist syntax. The parser operates via a novel solution method: it assembles an SMT model of an MG derivation, translates the inputs into SMT formulae that constrain the model, and then solves the model using the Z3 SMT-solver, a high-performance automatic theorem prover; as the SMT-model has finite size (being bounded by the inputs), it is decidable and thus solvable in finite time. The output derivation is then recovered from the model solution. To demonstrate this, we run the parser on several representative inputs and examine how the output derivations differ when the inputs are partially vs. fully specified. We conclude by discussing the parser’s extensibility and how a linguist can use it to automatically identify: (i) dependencies between input interface conditions and principles of syntax, and (ii) contradictions or redundancies between the model axioms encoding principles of syntax.
作为演绎的解析:使用自动定理证明器来解决一个极简解析器的SMT模型
我们为极简语法(MG)引入了一个基于约束的解析器,作为一个工作的计算机程序实现,它属于长期建立的“解析即演绎”框架。解析器将MG词典和(部分指定的)声音与意义的配对(即与语义表示配对的单词序列)作为输入,并使用公理化逻辑,声明性地推导出符合指定接口条件的语法派生(即解析树)。解析器建立在使用可满足模理论(Satisfiability Modulo Theories, SMT)的mg的第一个公理化之上,以基于约束的方式对极简语法原则进行编码。解析器通过一种新颖的求解方法进行操作:它组装一个MG派生的SMT模型,将输入转换为约束该模型的SMT公式,然后使用高性能自动定理证明器Z3 SMT求解器求解该模型;由于smt模型具有有限的大小(受输入的限制),因此它是可决定的,因此在有限时间内可求解。然后从模型解中恢复输出派生。为了演示这一点,我们在几个有代表性的输入上运行解析器,并检查输入部分指定与完全指定时输出派生的差异。最后,我们讨论了解析器的可扩展性,以及语言学家如何使用它来自动识别:(i)输入接口条件和语法原则之间的依赖关系,以及(ii)模型公理编码语法原则之间的矛盾或冗余。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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