Proceedings of CoNLL - 99 , Bergen , Norway pp 53 - 60 Memory � Based Shallow Parsing

نویسندگان

  • Walter Daelemans
  • Sabine Buchholz
  • Jorn Veenstra
چکیده

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

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Learning Transformation Rules to Find Grammatical Relations

Appears in Computational Natural Language Learning (CoNLL-99), pages 43-52. A workshop at the 9th Conf. of the European Chapter of the Assoc. for Computational Linguistics (EACL-99). Bergen, Norway, June, 1999. cs.CL/9906015 Grammatical relationships are an important level of natural language processing. We present a trainable approach to find these relationships through transformation sequence...

متن کامل

Memory-Based Shallow Parsing

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 t...

متن کامل

Shallow Parsing as Part-of-Speech Tagging

Treating shallow parsing as part-of-speech tagging yields results comparable with other, more elaborate approaches. Using the CoNLL 2000 training and testing material, our best model had an accuracy of 94.88%, with an overall FB1 score of 91.94%. The individual FB1 scores for NPs were 92.19%, VPs 92.70% and PPs 96.69%.

متن کامل

A Shallow Discourse Parsing System Based On Maximum Entropy Model

This paper describes our system for Shallow Discourse Parsing the CoNLL 2015 Shared Task. We regard this as a classification task and build a cascaded system based on Maximum Entropy to identify the discourse connective, the spans of two arguments and the sense of the discourse connective. We trained the cascaded models with a variety of features such as lexical and syntactic features. We also ...

متن کامل

SoNLP-DP System for ConLL-2016 English Shallow Discourse Parsing

This paper describes the submitted English shallow discourse parsing system from the natural language processing (NLP) group of Soochow university (SoNLP-DP) to the CoNLL-2016 shared task. Our System classifies discourse relations into explicit and non-explicit relations and uses a pipeline platform to conduct every subtask to form an end-to-end shallow discourse parser in the Penn Discourse Tr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016