Exploiting semantic dependencies in parsing
نویسنده
چکیده
In this paper we describe a semantic dependency model for estimating probabilities in a stochastic TAG parser (Resnik, 1992) (Schabes, 1992), and we compare it with the syntactic dependency model inherent in a TAG derivation using the flat treatment of modifiers described in (Schabes and Shieber, 1994).
منابع مشابه
برچسبزنی 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 کاملParsing Syntactic and Semantic Dependencies with Two Single-Stage Maximum Entropy Models
This paper describes our system to carry out the joint parsing of syntactic and semantic dependencies for our participation in the shared task of CoNLL-2008. We illustrate that both syntactic parsing and semantic parsing can be transformed into a word-pair classification problem and implemented as a single-stage system with the aid of maximum entropy modeling. Our system ranks the fourth in the...
متن کاملA Combined Memory-Based Semantic Role Labeler of English
In this paper we describe the system submitted to the closed challenge of the CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies. The system that we present extracts syntactic and semantic dependencies independently. Syntactic dependencies are processed with the MaltParser 0.4. Semantic dependencies are processed with a combination of memory-based classifiers. We foc...
متن کاملMultilingual Dependency Learning: Exploiting Rich Features for Tagging Syntactic and Semantic Dependencies
This paper describes our system about multilingual syntactic and semantic dependency parsing for our participation in the joint task of CoNLL-2009 shared tasks. Our system uses rich features and incorporates various integration technologies. The system is evaluated on in-domain and out-of-domain evaluation data of closed challenge of joint task. For in-domain evaluation, our system ranks the se...
متن کاملAn Iterative Approach for Joint Dependency Parsing and Semantic Role Labeling
We propose a system to carry out the joint parsing of syntactic and semantic dependencies in multiple languages for our participation in the shared task of CoNLL-2009. We present an iterative approach for dependency parsing and semantic role labeling. We have participated in the closed challenge, and our system achieves 73.98% on labeled macro F1 for the complete problem, 77.11% on labeled atta...
متن کامل