IHS-RD-Belarus at SemEval-2016 Task 9: Transition-based Chinese Semantic Dependency Parsing with Online Reordering and Bootstrapping

نویسندگان

  • Artsiom Artsymenia
  • Palina Dounar
  • Maria Yermakovich
چکیده

This paper is a description of our system developed for SemEval-2016 Task 9: Chinese Semantic Dependency Parsing. We have built a transition-based dependency parser with online reordering, which is not limited to a tree structure and can produce 99.7% of the necessary dependencies while maintaining linear algorithm complexity. To improve parsing quality we used additional techniques such as preand post-processing of the dependency graph, bootstrapping and a rich feature set with additional semantic features.

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

IHS-RD-Belarus at SemEval-2016 Task 1: Multistage Approach for Measuring Semantic Similarity

This paper describes the system for rating the degree of semantic equivalence between two text snippets developed by IHS-RD-Belarus for the SemEval 2016 STS shared task (Task 1). To predict the human ratings of text similarity we use a support vector regression model with multiple features representing similarity and difference scores calculated for each

متن کامل

IHS-RD-Belarus at SemEval-2016 Task 5: Detecting Sentiment Polarity Using the Heatmap of Sentence

This paper describes the system submitted by IHS-RD-Belarus team for the sentiment detection polarity subtask on Aspect Based Sentiment Analysis task at the SemEval 2016 workshop on semantic evaluation. We developed a system based on artificial neural network to detect the sentiment polarity of opinions. Evaluation on the test data set showed that our system achieved the F-score of 0.83 for res...

متن کامل

OSU_CHGCG at SemEval-2016 Task 9 : Chinese Semantic Dependency Parsing with Generalized Categorial Grammar

This paper introduces our Chinese semantic dependency parsing system for Task 9 of SemEval 2016. Our system has two components: a parser trained using the Berkeley Grammar Trainer on the Penn Chinese Treebank reannotated in a Generalized Categorial Grammar, and a multinomial logistic regression classifier. We first parse the data with the automatic parser to obtain predicate-argument dependenci...

متن کامل

Transition-Based Chinese Semantic Dependency Graph Parsing

Chinese semantic dependency graph is extended from semantic dependency tree, which uses directed acyclic graphs to capture richer latent semantics of sentences. In this paper, we propose two approaches for Chinese semantic dependency graph parsing. In the first approach, we build a non-projective transition-based dependency parser with the Swap-based algorithm. Then we use a classifier to add a...

متن کامل

IHS-RD-Belarus: Identification and Normalization of Disorder Concepts in Clinical Notes

This paper describes clinical disorder recognition and encoding system submitted by IHS R&D Belarus team at the SemEval-2015 shared task related to analysis of clinical texts. Our system is based on IHS Goldfire Linguistic Processor and uses a rich set of lexical, syntactic and semantic features. The proposed system consists of two components: a CRF-based approach to recognize disorder entities...

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