Linguistic Processing Pipelines: Problems and Solutions
نویسنده
چکیده
Many of the typical tasks in linguistic processing pipelines can be done with tools from OpenNLP (http://opennlp.sourceforge.net). There are OpenNLP components for sentence detection, tokenization, part-of-speech tagging, phrase chunking, syntactic parsing, named entity recognition, and coreference resolution. These tools have been widely used for several years, and form a good basis for illustrating issues in configuring linguistic processing pipelines. The paper compares several different approaches to creating pipelines based on the tools. OpenNLP tools use maximum entropy-based statistical language models. Recent versions of OpenNLP provide ready-made models for several languages, including German.
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