By Pierre M. Nugues

The parts of traditional language processing and computational linguistics have endured to develop lately, pushed by means of the call for to instantly method textual content and spoken info. With the processing energy and methods now on hand, examine is scaling up from lab prototypes to real-world, confirmed applications.This e-book teaches the rules of average language processing, first overlaying linguistics matters resembling encoding, entropy, and annotation schemes; defining phrases, tokens and elements of speech; and morphology. It then information the language-processing features concerned, together with part-of-speech tagging utilizing ideas and stochastic ideas; utilizing Prolog to jot down phase-structure grammars; parsing concepts and syntactic formalisms; semantics, predicate good judgment and lexical semantics; and research of discourse, and functions in conversation structures. the major characteristic of the e-book is the author's hands-on method all through, with broad workouts, pattern code in Prolog and Perl, and a close advent to Prolog. The reader is supported with a better half web site that includes instructing slides, courses, and extra material.The publication is acceptable for researchers and scholars of traditional language processing and computational linguistics.

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Additional info for An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German

Example text

These are devices that accept – recognize – or reject an input stream of characters. FSA are very efficient in terms of speed and memory occupation and are easy to implement in Prolog. In addition to text searching, they have many other applications: morphological parsing, part-of-speech annotation, and speech processing. 1 shows a three-state automaton numbered from 0 to 2, where state q0 is called the start state and q2 the final state. An automaton has a single start state and any number of final states, indicated by double circles.

Some models have also been misleading. This explains somewhat the failures of early attempts in language processing. In addition, many of the potential theories require massive computing power. Processors and storage able to support the implementation of complex models with substantial dictionaries, corpora, and parsers were not widely available until recently. However, in the last decade models have matured, and computing power has become inexpensive. ) perfect, they now enable us to obtain exploitable results.

When an automaton has the choice between two or more states, it selects one of them and remembers the state where it made the decision: the choice point. If it subsequently fails, the automaton backtracks to the choice point and selects another state to go to. In our example in Fig. 3, if the automaton moves first to state q2 with the string bb, it will end up in a state without outgoing transition. It will have to backtrack and select state q1 . Backtracking is precisely the strategy that Prolog uses automatically.

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