Consistent CCG Parsing over Multiple Sentences for Improved Logical Reasoning

Abstract

In formal logic-based approaches to Recognizing Textual Entailment (RTE), a Combinatory Categorial Grammar (CCG) parser is used to parse input premises and hypotheses to obtain their logical formulas. Here, it is important that the parser processes the sentences consistently; failing to recognize a similar syntactic structure results in inconsistent predicate argument structures among them, in which case the succeeding theorem proving is doomed to failure. In this work, we present a simple method to extend an existing CCG parser to parse a set of sentences consistently, which is achieved with an inter-sentence modeling with Markov Random Fields (MRF). When combined with existing logic-based systems, our method always shows improvement in the RTE experiments on English and Japanese languages.

Supertagging Combinatory Categorial Grammar with Attentive Graph Convolutional Networks

“…Combinatory categorial grammar (CCG) is a lexicalized grammatical formalism, where the lexical categories (also known as supertags) of the words in a sentence provide informative syntactic and semantic knowledge for text understanding. Therefore, CCG parse often provides useful information for many downstream natural language processing (NLP) tasks such as logical reasoning (Yoshikawa et al, 2018) and semantic parsing (Beschke, 2019). To perform CCG parsing in different languages, most studies conducted a supertagging-parsing pipline (Clark and Curran, 2007;Kummerfeld et al, 1 Our code and models for CCG supertagging are released at https://github.com/cuhksz-nlp/NeST-CCG.…”

Supertagging Combinatory Categorial Grammar with Attentive Graph Convolutional Networks

“…Combinatory categorial grammar (CCG) is a lexicalized grammatical formalism, where the lexical categories (also known as supertags) of the words in a sentence provide informative syntactic and semantic knowledge for text understanding. Therefore, CCG parse often provides useful information for many downstream natural language processing (NLP) tasks such as logical reasoning (Yoshikawa et al, 2018) and semantic parsing (Beschke, 2019). To perform CCG parsing in different languages, most studies conducted a supertagging-parsing pipline (Clark and Curran, 2007;Kummerfeld et al, † Corresponding author.…”