Memory-Based Shallow Parsing
نویسندگان
چکیده
We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving the performance of the memory-based learner. Our approach is evaluated on standard data sets and the results are compared with that of other systems. This reveals that our approach works well for base phrase identification while its application towards recognizing embedded structures leaves some room for improvement.
منابع مشابه
Proceedings of CoNLL - 99 , Bergen , Norway pp 53 - 60 Memory � Based Shallow Parsing
We present a memory based learning MBL approach to shallow parsing in which POS tagging chunking and identi cation of syntactic relations are formulated as memory based modules The experiments reported in this paper show competitive results the F for the Wall Street Journal WSJ treebank is for NP chunking for VP chunking for subject detection and for object detection
متن کاملA Memory-Based Shallow Parser for Spoken Dutch
We describe the development of a Dutch memory-based shallow parser. The availability of large treebanks for Dutch, such as the one provided by the Spoken Dutch Corpus, allows memory-based learners to be trained on examples of shallow parsing taken from the treebank, and act as a shallow parser after training. An overview is given of a modular memory-based learning approach to shallow parsing, c...
متن کاملShapaqa: Shallow Parsing for Question Answering on the World Wide Web
We introduce shapaqa, a shallow parsing approach to online, open-domain question answering on the WorldWideWeb. Given a form-based natural language question as input, the system uses a memory-based shallow parser to analyze web pages retrieved using normal keyword search on a search engine. Two versions of the system are evaluated on a test set of 200 questions. In combination with two back-oo ...
متن کاملبرچسبزنی خودکار نقشهای معنایی در جملات فارسی به کمک درختهای وابستگی
Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...
متن کامل