By Xiaofei Lu
In the earlier few a long time using more and more huge textual content corpora has grown quickly in language and linguistics examine. This was once enabled by means of impressive strides in average language processing (NLP) expertise, expertise that allows desktops to immediately and successfully method, annotate and study quite a lot of spoken and written textual content in linguistically and/or pragmatically significant methods. It has develop into superior than ever prior to for language and linguistics researchers who use corpora of their learn to achieve an enough realizing of the proper NLP expertise to take complete good thing about its capabilities.
This quantity presents language and linguistics researchers with an obtainable creation to the state of the art NLP know-how that allows automated annotation and research of huge textual content corpora at either shallow and deep linguistic degrees. The ebook covers quite a lot of computational instruments for lexical, syntactic, semantic, pragmatic and discourse research, including distinctive directions on find out how to receive, set up and use every one device in numerous working platforms and structures. The ebook illustrates how NLP know-how has been utilized in contemporary corpus-based language reports and indicates powerful how one can greater combine such know-how in destiny corpus linguistics research.
This ebook presents language and linguistics researchers with a helpful reference for corpus annotation and analysis.
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Additional info for Computational Methods for Corpus Annotation and Analysis
The second example below prints all three fields with the order of the second field and the third field switched. The third example below changes the value of the second field to the first character of the part-of-speech tag. The last example below prints all three fields and adds a fourth field (the logarithm of the word’s frequency). Note that in all four examples, we have included three lines of output for illustration purposes. The last two examples also show that you can perform different operations on the fields and report the results of those operations in the action statements.
Given the many POS taggers that exist, it is impractical to cover all of them in great detail. 3 Noun categories in the C7 Tagset. A. 6 NNB Preceding noun of title Mr. 7 NNL1 Singular locative noun Island 8 NNL2 Plural locative noun Islands 9 NNO Numeral noun, neutral for number Hundred 10 NNO2 Numeral noun, plural Hundreds 11 NNT1 Temporal noun, singular Day 12 NNT2 Temporal noun, plural Days 13 NNU Unit of measurement, neutral for number Cc 14 NNU1 Singular unit of measurement Inch 15 NNU2 Plural unit of measurement Feet 16 NP Proper noun, neutral for number IBM 17 NP1 Plural proper noun Koreas 18 NPD1 Singular weekday noun Sunday 19 NPD2 Plural weekday noun Sundays 20 NPM1 Singular month noun October 21 NPM2 Plural month noun Octobers to use than to have vague knowledge about many different taggers.
A specific word, phrase or string of characters). This is where regular expressions become useful. Regular expressions are sequences of characters that specify patterns, and they can be used in UNIX tools such as egrep to search for patterns in text, to replace strings that match specified patterns with something else, as well as to manipulate strings in text in many other useful ways. , basic and extended regular expressions. For a comprehensive introduction to regular expressions, including the types of regular expressions used in scripting languages such as Perl and Python, see Friedl (2006).