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Interactive grammar analysis of historical texts: Adaptive annotation approach to reconstruct the grammatical elaboration of Middle Low German (InterGramm)

历史文本的交互式语法分析：重构中古低地德语语法阐述的自适应注释方法 (InterGramm)

基本信息

批准号：
317446073
负责人：
Professorin Dr. Michaela Geierhos
金额：
--
依托单位：
Bereich Germanistische und Allgemeine Sprachwissenschaft
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/317446073?language=en
关键词：
Interactive grammar analysis historical texts

项目摘要

Our research project investigates the (structural) elaboration of Middle Low German (MLG) from the 13th century to the written language shift (16/17th century). During this period (16/17th century) MLG lost its dominant position as a supraregional written language accompanied with the growing influence of (written) Early New High German (ENHG). The study makes an important contribution to the reconstruction of grammatical developments in written MLG, which are - until now - examined only to some extent. For several reasons the study focuses on urban legal statutes: We assume that processes of language elaboration can be investigated especially in legal texts. They have to construe complex (legal) issues understandable independent of contextual information, so that elaborated linguistic structures capable of such a construal must be developed. These legal issues are particularly conditional relations; consequently, we are able to examine changes concerning the linguistic construction of conditionality during the investigation period. Furthermore, legal statutes are locatable and dateable, with the result that developmental dynamics of elaboration processes can be spatio-temporally reconstructed. Existing parsing and tagging systems of computational and corpus linguistics require static (a priori defined) grammars and grammatical categories, which does not cope with the historical dynamics of grammar. To solve one of the most central problems of existing annotation tools for historical texts, we plan to develop an interactive computational tool that combines machine learning and expert feedback. Using rule-based text analysis techniques and machine learning methods for "discovering" an evolving, dynamic grammar, and thereby reconstructing language change in an evidence-based way, is a novelty. Since this presupposes both historical language knowledge and skills in computational linguistics and computer sciences, the project requires a close cooperation of disciplines over the entire period of funding. Our empirical base consists of dateable and locatable legal texts from the 13th to the 17th century, building a corpus that is divided into the following subcorpora: The subcorpus MLG (main corpus) consists of Middle Low German texts from 1227 to 1650 and includes about 1.2 million words. The subcorpus ENHG consists of a selection of the first Early New High German texts arising in the Low German language area after the written language shift. This subcorpus includes 400,000 words. Our aim is to verify the assumption that these Early New High German texts instantiate - despite an ENHG lexis - a Middle Low German syntax/grammar.

我们的研究项目调查了从13世纪到书面语言转变（16/17世纪）的中古低地德语（MLG）的（结构）阐述。在这一时期（16/17世纪），MLG失去了其作为超区域书面语言的主导地位，伴随着（书面）早期新高地德语（ENHG）的影响力不断增长。这项研究对重建书面语篇中的语法发展做出了重要贡献，而到目前为止，这些语法发展只在一定程度上得到了检验。由于几个原因，研究重点放在城市法律的法规：我们认为，语言的加工过程可以调查，特别是在法律的文本。他们必须将复杂的（法律的）问题独立于语境信息之外加以理解，因此必须开发出能够进行这种理解的精心设计的语言结构。这些法律的问题特别是条件关系，因此，我们能够检查有关的语言建设的条件在调查期间的变化。此外，法律的法规是可定位和可定日期的，其结果是，发展动态的阐述过程可以时空重建。现有的计算语言学和语料库语言学的句法分析和标注系统需要静态的（先验定义的）语法和语法范畴，这并不科普语法的历史动态。为了解决现有历史文本注释工具的最核心问题之一，我们计划开发一种结合机器学习和专家反馈的交互式计算工具。使用基于规则的文本分析技术和机器学习方法来“发现”一种不断发展的动态语法，从而以基于证据的方式重建语言变化，这是一种新奇。由于这需要历史语言知识和计算语言学和计算机科学的技能，因此该项目需要在整个资助期间进行学科的密切合作。我们的经验基础包括日期和定位的法律的文本从13日至17日世纪，建立一个语料库，分为以下子语料库：子语料库MLG（主语料库）由中古低地德语文本从1227年到1650年，包括约120万字。子语料库ENHG包括一个选择的第一个早期新高地德语文本出现在低德语语言区后，书面语言的转变。这个子语料库包括40万个单词。我们的目的是验证的假设，这些早期的新高地德语文本实例化-尽管ENHG词汇-中低地德语语法/语法。