An Improved Semantic Role Labeling for Myanmar Text
نویسندگان
چکیده
منابع مشابه
Text Rewriting Improves Semantic Role Labeling
Large-scale annotated corpora are a prerequisite to developing high-performance NLP systems. Such corpora are expensive to produce, limited in size, often demanding linguistic expertise. In this paper we use text rewriting as a means of increasing the amount of labeled data available for model training. Our method uses automatically extracted rewrite rules from comparable corpora and bitexts to...
متن کاملSemantic Role Labeling Approach for Evaluation of Text Coherence
Detection of semantic roles associated with linguistic elements is important to the textual classification of communicative context into specific identities. In this paper, a new model for semantically identifying sentences is presented through contextual patterns. The proposed contextual pattern originated its structure from a labeling process of the semantic roles provided by constituents of ...
متن کاملDomain adaptation for semantic role labeling of clinical text
OBJECTIVE Semantic role labeling (SRL), which extracts a shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding natural language. Few studies in SRL have been conducted in the medical domain, primarily due to lack of annotated clinical SRL corpora, which are time-consuming and costly to build. The goal of this study i...
متن کاملText Mining for Open Domain Semi-Supervised Semantic Role Labeling
The identification and classification of some circumstance semantic roles like Location, Time, Manner and Direction, a task of Semantic Role Labeling (SRL), plays a very important role in building text understanding applications. However, the performance of the current SRL systems on those roles is often very poor, especially when the systems are applied on domains other than the ones they are ...
متن کاملText Rewriting Improves Semantic Role Labeling (Extended Abstract)
Large-scale annotated corpora are a prerequisite to developing high-performance NLP systems. Such corpora are expensive to produce, limited in size, often demanding linguistic expertise. In this paper we use text rewriting as a means of increasing the amount of labeled data available for model training. Our method uses automatically extracted rewrite rules from comparable corpora and bitexts to...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Networked and Distributed Computing
سال: 2019
ISSN: 2211-7946
DOI: 10.2991/ijndc.k.190326.001