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Semantic Role Labeling

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Release : 2011-02-02
Genre : Computers
Kind : eBook
Book Rating : 321/5 ( reviews)

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Book Synopsis Semantic Role Labeling by : Martha Palmer

Download or read book Semantic Role Labeling written by Martha Palmer. This book was released on 2011-02-02. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applying both supervised and unsupervised machine learning to this task, with a description of the standard stages and feature choices, as well as giving details of several specific systems. Recent advances include the use of joint inference to take advantage of context sensitivities, and attempts to improve performance by closer integration of the syntactic parsing task with semantic role labeling. Chapter 3 also discusses the impact the granularity of the semantic roles has on system performance. Having outlined the basic approach with respect to English, Chapter 4 goes on to discuss applying the same techniques to other languages, using Chinese as the primary example. Although substantial training data is available for Chinese, this is not the case for many other languages, and techniques for projecting English role labels onto parallel corpora are also presented. Table of Contents: Preface / Semantic Roles / Available Lexical Resources / Machine Learning for Semantic Role Labeling / A Cross-Lingual Perspective / Summary

Semantic Features for Semantic Role Labeling

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Author :
Release : 2011
Genre : Semantics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Semantic Features for Semantic Role Labeling by : Liam R. McGrath

Download or read book Semantic Features for Semantic Role Labeling written by Liam R. McGrath. This book was released on 2011. Available in PDF, EPUB and Kindle. Book excerpt:

Semantic Role Labeling Using Rich Morphological Features

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Author :
Release : 2013
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Semantic Role Labeling Using Rich Morphological Features by :

Download or read book Semantic Role Labeling Using Rich Morphological Features written by . This book was released on 2013. Available in PDF, EPUB and Kindle. Book excerpt:

Hands-On Natural Language Processing with Python

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Author :
Release : 2018-07-18
Genre : Computers
Kind : eBook
Book Rating : 915/5 ( reviews)

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Book Synopsis Hands-On Natural Language Processing with Python by : Rajesh Arumugam

Download or read book Hands-On Natural Language Processing with Python written by Rajesh Arumugam. This book was released on 2018-07-18. Available in PDF, EPUB and Kindle. Book excerpt: Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Semantic Role Labeling

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Author :
Release : 2022-05-31
Genre : Computers
Kind : eBook
Book Rating : 355/5 ( reviews)

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Book Synopsis Semantic Role Labeling by : Martha Palmer

Download or read book Semantic Role Labeling written by Martha Palmer. This book was released on 2022-05-31. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applying both supervised and unsupervised machine learning to this task, with a description of the standard stages and feature choices, as well as giving details of several specific systems. Recent advances include the use of joint inference to take advantage of context sensitivities, and attempts to improve performance by closer integration of the syntactic parsing task with semantic role labeling. Chapter 3 also discusses the impact the granularity of the semantic roles has on system performance. Having outlined the basic approach with respect to English, Chapter 4 goes on to discuss applying the same techniques to other languages, using Chinese as the primary example. Although substantial training data is available for Chinese, this is not the case for many other languages, and techniques for projecting English role labels onto parallel corpora are also presented. Table of Contents: Preface / Semantic Roles / Available Lexical Resources / Machine Learning for Semantic Role Labeling / A Cross-Lingual Perspective / Summary

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