Natural Language Processing and Computational Linguistics 2: Semantics, Discourse and Applications

ISBN-13: 9781848219212 / Angielski / Twarda / 2018 / 318 str.

Zakaria Kurdi

Opis

Natural Language Processing (NLP) is a scientific discipline which is found at the intersection of fields such as Artificial Intelligence, Linguistics, and Cognitive Psychology. This book presents in four chapters the state of the art and fundamental concepts of key NLP areas. Are presented in the first chapter the fundamental concepts in lexical semantics, lexical databases, knowledge representation paradigms, and ontologies. The second chapter is about combinatorial and formal semantics. Discourse and text representation as well as automatic discourse segmentation and interpretation, and anaphora resolution are the subject of the third chapter. Finally, in the fourth chapter, I will cover some aspects of large scale applications of NLP such as software architecture and their relations to cognitive models of NLP as well as the evaluation paradigms of NLP software. Furthermore, I will present in this chapter the main NLP applications such as Machine Translation (MT), Information Retrieval (IR), as well as Big Data and Information Extraction such as event extraction, sentiment analysis and opinion mining.

Spis treści

Introduction  ix

Chapter 1. The Sphere of Lexicons and Knowledge   1

1.1. Lexical semantics 1

1.1.1. Extension of lexical meaning 1

1.1.2. Paradigmatic relations of meaning  6

1.1.3. Theories of lexical meaning 16

1.2. Lexical databases 23

1.2.1. Standards for encoding and exchanging data 25

1.2.2. Standard character encoding 25

1.2.3. Content standards  32

1.2.4. Writing systems  40

1.2.5. A few lexical databases 45

1.3. Knowledge representation and ontologies 49

1.3.1. Knowledge representation  49

1.3.2. Ontologies  63

Chapter 2. The Sphere of Semantics  75

2.1. Combinatorial semantics 75

2.1.1. Interpretive semantics 75

2.1.2. Generative semantics 80

2.1.3. Case grammar 82

2.1.4. Rastier’s interpretive semantics  84

2.1.5. Meaning–text theory 92

2.2. Formal semantics 95

2.2.1. Propositional logic 95

2.2.2. First–order logic  106

2.2.3. Lambda calculus  113

2.2.4. Other types of logic 121

Chapter 3. The Sphere of Discourse and Text  123

3.1. Discourse analysis and pragmatics 123

3.1.1. Fundamental concepts 123

3.1.2. Utterance production 125

3.1.3. Context, cotext and intertextuality  128

3.1.4. Information structure in discourse  130

3.1.5. Coherence  137

3.1.6. Cohesion  138

3.1.7. Ellipses   142

3.1.8. Textual sequences  143

3.1.9. Speech acts  144

3.2. Computational approaches to discourse  146

3.2.1. Linear segmentation of discourse  146

3.2.2. Rhetorical structure theory and automatic discourse analysis  148

3.2.3. Discourse interpretation: DRT 154

3.2.4. Processing anaphora 159

Chapter 4. The Sphere of Applications  169

4.1. Software engineering for NLP software  169

4.1.1. Lifecycle of an NLP software 169

4.1.2. Software architecture for NLP 170

4.1.3. Serial architectures 171

4.1.4. Data–centered architectures 173

4.1.5. Object–oriented architectures 177

4.1.6. Multi–agent architectures 178

4.1.7. Syntactic–semantic cooperation: from cognitive models to software architecture 180

4.1.8. Programming languages for NLP  184

4.1.9. Evaluation of NLP systems 186

4.2. Machine translation (MT) 191

4.2.1. Why is translation difficult? 192

4.2.2. History of MT systems 194

4.2.3. Typology of MT systems 196

4.2.4. The use of MT 198

4.2.5. MT techniques  199

4.2.6. Example of a translation system: Verbmobil 208

4.3. Information retrieval (IR) 211

4.3.1. IR and related domains 211

4.3.2. Lexical information and IR 213

4.3.3. Information retrieval approaches  219

4.4. Big Data (BD) and information extraction  234

4.4.1. Structured, semi–structured and unstructured data 234

4.4.2. Architectures of BD processing systems  235

4.4.3. Role of NLP in BD processing  237

4.4.4. Information extraction 238

Conclusion  259

Bibliography  263

Index 301