Linguistic Resources for Natural Language Processing: On the Necessity of Using Linguistic Methods to Develop NLP Software

Foreword
Preface
About This Book
Contents
Part I: Introduction
	The Limitations of Corpus-Based Methods in NLP
		1 Introduction
			1.1 Training Corpora
			1.2 Limited Tag Sets
			1.3 Reliability of Training Corpora
		2 NLP Software Results
			2.1 Incorrect Tags
			2.2 Concepts, Themes, and Terms
			2.3 Word Clouds
			2.4 Semantic Networks
		3 Principles at the Basis of Empirical Methods
			3.1 Flawed Principle: The Notion of Similar Contexts
			3.2 Flawed Principle: The Units of Processing
		4 The Scientific Approach
			4.1 The Real Value of a Training Corpus
		5 Conclusion
		References
Part II: Developing Linguistic-Based NLP Software
	Linguistic Resources for the Automatic Generation of Texts in Natural Language: The Elvex Formalism
		1 Introduction
		2 A Hypothetico-deductive Approach of NLG
			2.1 A Deterministic Model
			2.2 A Declarative and Constraint-Based Approach
			2.3 A Monotonic Model
		3 Writing a Grammar with Elvex
			3.1 Feature Structure
			3.2 Constituent-Structure (C-Structure)
			3.3 Syntactic Rules
			3.4 The Lexicon
				The Morphological Lexicon Defined by Extension
				The Pattern Lexicon
			3.5 The Language Rules
			3.6 The Speaker´s Rules and Language
		4 Conclusion
		References
	Towards a More Efficient Arabic-French Translation
		1 Introduction
		2 Related Works
		3 Problems in Arabic Named Entities
			3.1 Problems in Recognition
			3.2 Problems with the Translation of Arabic NEs
		4 Implementation of the Set of Transducers
			4.1 Recognition Phase
			4.2 Translation Phase
		5 Experimentation and Evaluation
			5.1 Experimentation of Recognition Phase
			5.2 Experimentation of Translation Phase
		6 From the NEs Recognition to the Translation of Complex Sentences
			6.1 NEs and Relative Clauses
			6.2 Implemented Resources
			6.3 Experimentation of Implemented Resources
		7 Conclusion and Perspectives
		References
	Linguistic Resources and Methods for Belarusian Natural Language Processing
		1 Introduction
		2 Text-to-Speech Synthesizer
		3 The Transcription Generator
		4 Word Paradigm Generator
		5 Conclusion
		References
Part III: Linguistic Resources for Low-Resource Languages
	A New Set of Linguistic Resources for Ukrainian
		1 Introduction
		2 Theoretical Basis
			2.1 Approaches to Designing Natural Language Processing Applications
		3 Statistical Tools for Ukrainian
			3.1 Sketch ENGINE
			3.2 TreeTagger and RNNTagger
		4 Ukrainian Linguistic Resources
			4.1 Dictionary
			4.2 Morphological Grammars
		5 Conclusion and Perspectives
		References
	Formalization of the Quechua Morphology
		1 Introduction
		2 Constructing Electronic Dictionaries
			2.1 Formalization of Quechua Noun Inflections
			2.2 Formalizing Quechua Verb Morphology
			2.3 Formalizing Adjective Morphology
			2.4 Formalizing Adverbs Morphology
			2.5 Formalizing Pronouns Morphology
		3 Conclusion and Perspectives
		References
	The Challenging Task of Translating the Language of Tango
		1 Introduction
		2 The Project: Automatic Machine Translation
		3 Translation of Terms
		4 Translating Syntactic Structures
		5 Conclusion
		References
	A Polylectal Linguistic Resource for Rromani
		1 Introduction
			1.1 Rromani Dialectology
			1.2 Rromani Alphabet
			1.3 Rromani Dictionaries
			1.4 Rromani Language Lessons
			1.5 Rromani Grammar
		2 Empirical NLP Software
			2.1 Rromani, a Low-Resource Language
		3 Rromani Online Resources
			3.1 Russian Romani Corpus
			3.2 ROMLEX
			3.3 Online Rromani Dictionaries
			3.4 Need for Coherent Linguistic Resources
		4 Rromani Linguistic Resources
			4.1 Dictionary
			4.2 Morphology
		5 Evaluation and Perspectives
		References
Part IV: Processing Multiword Units: The Linguistic Approach
	Using Linguistic Criteria to Define Multiword Units
		1 Introduction
		2 The Corpus-Based Approach and Collocations
		3 Semantic Atomicity
		4 Term Usage
		5 Idiosyncratic Transformational Analyses
		6 Conclusion
		References
	A Linguistic Approach to English Phrasal Verbs
		1 Introduction
		2 English Phrasal Verbs: Particle vs. Preposition
			2.1 Further Distinctions: Prepositional and Phrasal Prepositional Verbs
		3 Lexicon-Grammar of Phrasal Verbs
			3.1 Using Lexicon-Grammar in Tandem with NooJ
			3.2 Accuracy of Discontinuous Phrasal Verbs
		4 Removing False Phrasal Verbs Automatically
			4.1 PV Disambiguation Grammar 1: Environment to Right of ``PV´´
			4.2 PV Disambiguation Grammar 2: Environment to Left of ``PV´´
			4.3 PV Disambiguation Grammar 3: Locative Environment to Right of ``PV´´
		5 Conclusion
		References
	Analysis of Indonesian Multiword Expressions: Linguistic vs Data-Driven Approach
		1 Introduction
		2 POS Tagging
		3 Syntactic Parsing
		4 Machine Translation
		5 Conclusion
		References