RI: SMALL: Statistical Linguistic Typology

这个项目考虑了两种语言观点的统一：自然语言处理和语言类型学。我们的观点是，类型学信息对于解决现实世界的自然语言处理非常有用，并且可以从语言数据中自动导出。本研究首先探讨了如何使用语源学知识来提高低密度语言的依赖解析和机器翻译等问题的性能。直观地说，我们的统计模型浪费时间探索一个太大的假设空间：现实语法的空间比所有语法的空间要小得多。本研究的第二部分探讨了原始文本类型知识的自动获取和提升。本研究的结果是：(a)改进了硬自然语言处理问题的统计模型；(b)从数据中自动导出的更大的类型学共性库。我们的结果是根据原始语言处理任务和从数据中挖掘的通用含义的质量进行经验评估的，但将它们与已知的通用库进行比较。我们的研究结果将影响自然语言处理和语言学领域。从研究方面来看，这项研究将在比我们打算研究的问题更广泛的问题中找到应用；特别是，在自然语言处理技术中使用语言共性将从根本上改变该领域处理多语言的方式。从语言学的角度来看，这个项目的目标是揭示语言共性。这不仅会影响类型学领域，也会影响濒危语言的研究和保护。通过从数据中自动识别类型学特征和含义，记录濒危语言的过程可以更有效，从而减少这些语言知识的流失。

This project considers the unification of two view of language: thatfrom natural language processing and that from linguistic typology.Our view is that typological information is both useful for solvingreal-world natural language processing thats and automaticallyderivable from language data. This research first explores how to usetypological knowledge to improve performance on problems such asdependency parsing and machine translation for low density langauges.Intuitively, our statistical models waste time exploring a hypothesisspace that is too big: the space of realistic grammars is much smallerthan the space of all grammars. The second part of this researchconsiders the automatic acquisition and boostrapping of typologicalknowledge from raw text. The outcome of this research is: (a)improved statistical models for hard natural language processingproblems; and (b) a larger library of typological universals that havebeen derived automatically from data. Our outcomes are empiricallyevaluated on the raw language processing tasks and in terms of thequality of the universal implications mined from data, but comparingthem with known repositories of universals. Our results will impact the fields of natural language processing and linguistics. From the research side, this research will find applications in a wider variety of problems than the ones we intend to study; in particular, the use of linguistic universals in natural language processing technologywill fundamentally change the way multilinguality is addressed in thisfield. From a linguistics perspective, the goal of this project is toshed new light on linguistic universals. This should impact not onlythe area of typology, but also the study and preservation ofendangered languages. By automatically identifying typologicalfeatures and implications from data, the process of documentingendangered languages could be made more efficient: leading to asmaller loss of knowledge of these languages.