Description of predicative nouns in a Modern Greek financial corpus

This paper reports on a corpus-based description of predicative nouns in a register-diversified financial corpus. Structural linguistics (Chomsky 1981) and register analysis (Biber & Conrad 2009) are the theoretical backgrounds of this research. As predicative noun, we define a noun derived from a verb, an adjective or a noun that occurs in support verb constructions (Gross 1981).     In order to identify the predicative nouns occurring in a Modern Greek financial corpus we applied a. five Lexicon-Grammar tables containing predicative nouns, along with their distributional and transformational properties (Tziafa 2012); b. 122 finite state automata (Ioannidou 2013), representing noun phrases.

An investigation on Chinese noun phrase extraction.

Chan Kun-Chung Timothy.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 79-83).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Outline of Thesis --- p.3Chapter 2 --- Background --- p.5Chapter 2.1 --- Chinese Noun Phrase Structure --- p.5Chapter 2.2 --- Literature Review --- p.6Chapter 2.3 --- Observations --- p.10Chapter 2.4 --- Chapter Summary --- p.11Chapter 3 --- Maximal Chinese Noun Phrase Extraction System --- p.13Chapter 3.1 --- Background --- p.13Chapter 3.1.1 --- Part-of-speech Tagset --- p.13Chapter 3.1.2 --- The Tagging System --- p.14Chapter 3.1.3 --- Chinese Corpus --- p.16Chapter 3.1.4 --- Grammar Rules and Boundary Information --- p.17Chapter 3.1.5 --- Feature Selection --- p.19Chapter 3.2 --- Overview of Our Chinese Noun Phrase Extraction System --- p.19Chapter 3.2.1 --- Training --- p.19Chapter 3.2.2 --- Testing --- p.21Chapter 3.3 --- Chapter Summary --- p.21Chapter 4 --- Preliminary Noun Phrase Extraction --- p.23Chapter 4.1 --- Framework --- p.23Chapter 4.2 --- Boundary Information Acquisition --- p.24Chapter 4.3 --- Candidate Boundary Insertion --- p.26Chapter 4.4 --- Pairing of Candidate Boundaries --- p.27Chapter 4.4.1 --- Conditional Probability-based Model --- p.28Chapter 4.4.2 --- Heuristic-based Model --- p.29Chapter 4.4.3 --- Dynamic Programming-based Model --- p.30Chapter 4.4.4 --- Model Selection --- p.31Chapter 4.4.5 --- Revised Dynamic Programming Model --- p.32Chapter 4.4.6 --- Analysis of the Impact of the Revised DP Model --- p.35Chapter 4.4.7 --- Experiments of Dynamic Programming-based Model --- p.38Chapter 4.4.8 --- Result Analysis --- p.42Chapter 4.5 --- Concluding Remarks on DP-Based Model --- p.47Chapter 4.6 --- Chapter Summary --- p.49Chapter 5 --- Automatic Error Correction --- p.50Chapter 5.1 --- Introduction --- p.50Chapter 5.1.1 --- Statistical Properties of TEL --- p.54Chapter 5.1.2 --- Related Applications --- p.55Chapter 5.2 --- Settings of Main Components --- p.57Chapter 5.2.1 --- Initial State --- p.58Chapter 5.2.2 --- Transformation Actions --- p.58Chapter 5.2.3 --- Triggering Features of Transformation Templates --- p.58Chapter 5.2.4 --- Evaluation of Rule --- p.62Chapter 5.2.5 --- Stopping Threshold --- p.62Chapter 5.3 --- Experiments and Results --- p.63Chapter 5.3.1 --- Setup and Procedure --- p.63Chapter 5.3.2 --- Overall Performance --- p.63Chapter 5.3.3 --- Contribution of Rules --- p.67Chapter 5.3.4 --- Remarks on Rules Learning --- p.69Chapter 5.3.5 --- Discussion on Recall Performance --- p.70Chapter 5.4 --- Chapter Summary --- p.73Chapter 6 --- Conclusion --- p.74Chapter 6.1 --- Summary --- p.74Chapter 6.2 --- Contributions --- p.76Chapter 6.3 --- Future Work --- p.76Bibliography --- p.79Chapter A --- Chinese POS Tag Set --- p.84Chapter B --- Algorithms of Boundary Pairing Models --- p.88Chapter B.1 --- Heuristic based Model --- p.88Chapter B.2 --- Dynamic Programming based Model --- p.89Chapter C --- Triggering Environments of Transformation Templates --- p.9

An overview of theories of the syntax-phonology interface

This article is intended as a critical survey of the phonological theories of the syntax-phonology interface. These theories can be divided into two main groups, according to the role they attribute to syntactic representations in creating phonological domains. On the one hand there is the Direct Reference Theory, which claims that phonological operations are directly sensitive to syntactic information, in terms of relations of c-command or m-command (i.e., government) holding between the elements participating in phonological processes. On the other, there is the Prosodic Hierarchy Theory of Prosodic Phonology, which defends the view that syntactic and phonological representations are not isomorphic and that there is a distinct level of representation called Prosodic Structure which contains a hierarchically organized set of prosodic constituents. These constituents are built from syntactic structure by a finite set of parameterized algorithms, and phonological processes refer to prosodic constituents rather than to syntactic constituents. Elordieta (1997, 1999) proposes that certain phonological phenomena may be specified to apply in the domains or constituents formed by functional and lexical heads related by feature checking. Seidl's (2001) Minimal Indirect Reference Theory claims that syntactic relationships such as theta-domains determine phonological constituency at the phrasal level. Another important, more recent view is the one that maintains that spellout domains (that is, all the material included in a syntactic phase except for the head of the phase and elements in the specifier of that phase) are interpreted as phonological constituents in PF

An overview of theories of the syntax-phonology interface

This article is intended as a critical survey of the phonological theories of the syntax-phonology interface. These theories can be divided into two main groups, according to the role they attribute to syntactic representations in creating phonological domains. On the one hand there is the Direct Reference Theory, which claims that phonological operations are directly sensitive to syntactic information, in terms of relations of c-command or m-command (i.e., government) holding between the elements participating in phonological processes. On the other, there is the Prosodic Hierarchy Theory of Prosodic Phonology, which defends the view that syntactic and phonological representations are not isomorphic and that there is a distinct level of representation called Prosodic Structure which contains a hierarchically organized set of prosodic constituents. These constituents are built from syntactic structure by a finite set of parameterized algorithms, and phonological processes refer to prosodic constituents rather than to syntactic constituents. Elordieta (1997, 1999) proposes that certain phonological phenomena may be specified to apply in the domains or constituents formed by functional and lexical heads related by feature checking. Seidl's (2001) Minimal Indirect Reference Theory claims that syntactic relationships such as theta-domains determine phonological constituency at the phrasal level. Another important, more recent view is the one that maintains that spellout domains (that is, all the material included in a syntactic phase except for the head of the phase and elements in the specifier of that phase) are interpreted as phonological constituents in PF

Chinese noun phrase parsing with a hybrid approach.

by Angel Suet Yi Tse.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 126-130).AbstractAcknowledgementsTable of ContentsList of TablesList of FiguresPlagiarism DeclarationChapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Overview --- p.1Chapter 1.2 --- Motivation --- p.2Chapter 1.3 --- Applications of NP parsing --- p.4Chapter 1.4 --- The Hybrid Approach of NP Partial Parsing with Rule Set Derived from de NPs --- p.5Chapter 1.5 --- Organization of the Thesis --- p.7Chapter Chapter 2 --- Related Work --- p.9Chapter 2.1 --- Overview --- p.9Chapter 2.2 --- Chinese Versus English Languages --- p.10Chapter 2.3 --- Traditional Versus Contemporary Parsing Approaches --- p.15Chapter 2.3.1 --- Linguistics-based and Corpus-based Knowledge Acquisition --- p.15Chapter 2.3.2 --- Basic Processing Unit --- p.16Chapter 2.3.3 --- Related Literature --- p.17Chapter 2.4 --- Sentence / Free Text Parsing --- p.18Chapter 2.4.1 --- Linguistics-based --- p.18Chapter 2.4.2 --- Corpus-based --- p.21Chapter 2.5 --- NP Processing --- p.22Chapter 2.5.1 --- NP Detection --- p.22Chapter 2.5.2 --- NP Partial Parsing --- p.26Chapter 2.6 --- Summary --- p.27Chapter Chapter 3 --- Knowledge Elicitation for General NP Partial Parsing from De NPs --- p.28Chapter 3.1 --- Overview --- p.28Chapter 3.2 --- Background --- p.29Chapter 3.3 --- Research in De Phrases --- p.33Chapter 3.3.1 --- Research of de Phrases in Pure Linguistics --- p.33Chapter 3.3.2 --- Research in de Phrases in Computational Linguistics --- p.36Chapter 3.4 --- Significance of De Phrases --- p.37Chapter 3.4.1 --- Implication to General NP Parsing --- p.37Chapter 3.4.2 --- Embedded Knowledge for General NP Parsing --- p.37Chapter 3.5 --- Summary --- p.39Chapter Chapter 4 --- Knowledge Acquisition Approaches for General NP Partial Parsing --- p.40Chapter 4.1 --- Overview --- p.40Chapter 4.2 --- Linguistic-based Approach --- p.41Chapter 4.3 --- Corpus-based Approach --- p.43Chapter 4.3.1 --- Generalization of NP Grammatical Patterns --- p.44Chapter 4.3.2 --- Pitfall of Generalization --- p.47Chapter 4.4 --- The Hybrid Approach --- p.47Chapter 4.4.1 --- Combining Strategies --- p.50Chapter 4.4.2 --- Merging Techniques --- p.53Chapter 4.5 --- CNP3- The Chinese NP Partial Parser --- p.55Chapter 4.5.1 --- The NP Detection and Extraction Unit (DEU) --- p.56Chapter 4.5.2 --- The Knowledge Acquisition Unit (KAU) --- p.56Chapter 4.5.3 --- The Parsing Unit (PU) --- p.57Chapter 4.5.4 --- Internal Representation of Chinese NPs and Grammar Rules --- p.57Chapter 4.6 --- Summary --- p.58Chapter Chapter 5 --- "Experiments on Linguistics-, Corpus-based and the Hybrid Approaches" --- p.60Chapter 5.1 --- Overview --- p.60Chapter 5.2 --- Objective of Experiments --- p.61Chapter 5.3 --- Experimental Setup --- p.62Chapter 5.3.1 --- The Corpora --- p.62Chapter 5.3.2 --- The Standard and Extended Tag Sets --- p.64Chapter 5.4 --- Overview of Experiments --- p.67Chapter 5.5 --- Evaluation of Linguistic De NP Rules (Experiment 1 A) --- p.70Chapter 5.5.1 --- Method --- p.71Chapter 5.5.2 --- Results --- p.72Chapter 5.5.3 --- Analysis --- p.72Chapter 5.6 --- Evaluation of Corpus-based Approach (Experiment IB) --- p.74Chapter 5.6.1 --- Method --- p.74Chapter 5.6.2 --- Results --- p.75Chapter 5.6.3 --- Analysis --- p.76Chapter 5.6.4 --- Generalization of NP Grammatical Patterns (Experiment 1B'） --- p.76Chapter 5.6.5 --- Results after Merging of Rule Sets (Experiment 1C) --- p.77Chapter 5.6.6 --- Error Analysis --- p.79Chapter 5.7 --- Phase II Evaluation: Test on General NP Parsing (Experiment 2) --- p.82Chapter 5.7.1 --- Method --- p.83Chapter 5.7.2 --- Results --- p.85Chapter 5.7.3 --- Error Analysis --- p.86Chapter 5.8 --- Summary --- p.92Chapter Chapter 6 --- Reliability Evaluation of the Hybrid Approach --- p.94Chapter 6.1 --- Overview --- p.94Chapter 6.2 --- Objective --- p.95Chapter 6.3 --- The Training and Test Corpora --- p.96Chapter 6.4 --- The Knowledge Base --- p.98Chapter 6.5 --- Convergence Sequence Tests --- p.99Chapter 6.5.1 --- Results of Close Convergence Tests --- p.100Chapter 6.5.2 --- Results of Open Convergence Tests --- p.104Chapter 6.5.3 --- Conclusions with Convergence Tests --- p.106Chapter 6.6 --- Cross Evaluation Tests --- p.106Chapter 6.6.1 --- Results --- p.109Chapter 6.6.2 --- Conclusions with Cross Evaluation Tests --- p.112Chapter 6.7 --- Summary --- p.113Chapter Chapter 7 --- Discussion and Conclusions --- p.115Chapter 7.1 --- Overview --- p.115Chapter 7.2 --- Difficulties Encountered --- p.116Chapter 7.2.1 --- Lack of Standard in Part-of-speech Categorization in Chinese Language --- p.116Chapter 7.2.2 --- Under or Over-specification of Tag Class in Tag Set --- p.118Chapter 7.2.3 --- Difficulty in Nominal Compound NP Analysis --- p.119Chapter 7.3 --- Conclusions --- p.120Chapter 7.4 --- Future Work --- p.122Chapter 7.4.1 --- Full Automation of NP Pattern Generalization --- p.122Chapter 7.4.2 --- Incorporation of Semantic Constraints --- p.123Chapter 7.4.3 --- Computational Structural Analysis of Nominal Compound NP --- p.124References --- p.126Appendix A The Extended Tag Set --- p.131Appendix B Linguistic Grammar Rules --- p.135Appendix C Generalized Grammar Rules --- p.13