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EN
This article describes a method to analyze characters in a literary text by considering their verbal interactions. This method exploits techniques from computational linguistics to extract all direct speech from a treebank, and to build a conversational network that visualizes the speakers, the listeners and their degree of interaction. We apply this method to create and visualize a conversational network for the Chinese Buddhist Canon. We analyze the protagonists and their interlocutors, and report statistics on their number of utterances and types of listeners, how their speech was reported, and subcommunities in the network.
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EN
We start with the assumption that (i) a corpus represents the use of language, i.e. linguistic performance, (ii) a rule-based grammar represents language as a system, i.e. linguistic competence, and (iii) corpus annotation represents the interface between the two. To detect and diagnose mismatches between the language use and the language system we use a constraint-based grammar run as a constraint solver on texts tagged and dependency-parsed by stochastic tools. The texts also have MWEs (multi-word expressions) identified and transformed into a constituency-based format before the grammar is applied. We describe the role and results of the grammar, and its use to check texts annotated with morphosyntactic categories, syntactic structure and information about the status of relevant expressions as MWEs. The grammar also employs lexical resources such as a valency lexicon and a database of MWEs to make the checking more accurate and the annotation more informative. The results are represented as typed feature structures where MWE-related information can be shared by lexical and phrasal nodes. This allows for the annotation of MWEs as lexical units, independently of their analysis in terms of syntactic structure. Focusing on the interplay of MWEs with their syntactic context we analyse a number of representative examples, pointing out the pros and cons of specific solutions and the whole approach.
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