Corpus-Concordance-Database-VARBRUL'
Identifieur interne : 000461 ( Istex/Corpus ); précédent : 000460; suivant : 000462Corpus-Concordance-Database-VARBRUL'
Auteurs : John M. KirkSource :
- Literary and Linguistic Computing [ 0268-1145 ] ; 1994.
Abstract
Although concordances are in widespread use and have become the main output format of corpus analysis, they do little more than rearrange the selected data as a special kind of list. By yielding enough preceding and following context, however, concordances are usually sufficient for the purposes of classification and analysis. As items of high frequency have different senses, perform different functions, occur in differently constructed environments, and are thus used variably, classification is a major part of linguistic analysis. Up until now, however, it has. not been easy to store classificatory encodings alongside the concordance data, with a view to further exploitation of these encoded classifications. One solution is the importation of concordances into a database, where additional fields can then be created for mnemonic classificatory encodings, for further sorting on the basis of these encodings. This paper shows how this solution can be implemented in practice. It shows how concordances can come to be used in an ‘intelligent’ way as the basis of linguistic analysis; it also provides a practical tip for the use of the main software package for the analysis of interacting variables: VARBRUL For its quantitative and statistical correlation of co-occuring variants of different internal or external variables, VARBRUL depends utterly on a tokens file of encodings about the behaviour of each item. This paper shows how this tokens file can now be created by copying the classificatory encodings directly from the database.
Url:
DOI: 10.1093/llc/9.4.259
Links to Exploration step
ISTEX:BB91AA8C5A07C6FB65D07C0A1793123181B9E6FBLe document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title>Corpus-Concordance-Database-VARBRUL'</title>
<author wicri:is="90%"><name sortKey="Kirk, John M" sort="Kirk, John M" uniqKey="Kirk J" first="John M." last="Kirk">John M. Kirk</name>
<affiliation><mods:affiliation>The Queen's University of Belfast, Northern Ireland</mods:affiliation>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB</idno>
<date when="1994" year="1994">1994</date>
<idno type="doi">10.1093/llc/9.4.259</idno>
<idno type="url">https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/fulltext/pdf</idno>
<idno type="wicri:Area/Istex/Corpus">000461</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title level="a">Corpus-Concordance-Database-VARBRUL'</title>
<author wicri:is="90%"><name sortKey="Kirk, John M" sort="Kirk, John M" uniqKey="Kirk J" first="John M." last="Kirk">John M. Kirk</name>
<affiliation><mods:affiliation>The Queen's University of Belfast, Northern Ireland</mods:affiliation>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series><title level="j">Literary and Linguistic Computing</title>
<idno type="ISSN">0268-1145</idno>
<idno type="eISSN">1477-4615</idno>
<imprint><publisher>Oxford University Press</publisher>
<date type="published" when="1994">1994</date>
<biblScope unit="volume">9</biblScope>
<biblScope unit="issue">4</biblScope>
<biblScope unit="page" from="259">259</biblScope>
<biblScope unit="page" to="266">266</biblScope>
</imprint>
<idno type="ISSN">0268-1145</idno>
</series>
<idno type="istex">BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB</idno>
<idno type="DOI">10.1093/llc/9.4.259</idno>
<idno type="ArticleID">9.4.259</idno>
</biblStruct>
</sourceDesc>
<seriesStmt><idno type="ISSN">0268-1145</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass></textClass>
<langUsage><language ident="en">en</language>
</langUsage>
</profileDesc>
</teiHeader>
<front><div type="abstract">Although concordances are in widespread use and have become the main output format of corpus analysis, they do little more than rearrange the selected data as a special kind of list. By yielding enough preceding and following context, however, concordances are usually sufficient for the purposes of classification and analysis. As items of high frequency have different senses, perform different functions, occur in differently constructed environments, and are thus used variably, classification is a major part of linguistic analysis. Up until now, however, it has. not been easy to store classificatory encodings alongside the concordance data, with a view to further exploitation of these encoded classifications. One solution is the importation of concordances into a database, where additional fields can then be created for mnemonic classificatory encodings, for further sorting on the basis of these encodings. This paper shows how this solution can be implemented in practice. It shows how concordances can come to be used in an ‘intelligent’ way as the basis of linguistic analysis; it also provides a practical tip for the use of the main software package for the analysis of interacting variables: VARBRUL For its quantitative and statistical correlation of co-occuring variants of different internal or external variables, VARBRUL depends utterly on a tokens file of encodings about the behaviour of each item. This paper shows how this tokens file can now be created by copying the classificatory encodings directly from the database.</div>
</front>
</TEI>
<istex><corpusName>oup</corpusName>
<author><json:item><name>JOHN M. KIRK</name>
<affiliations><json:string>The Queen's University of Belfast, Northern Ireland</json:string>
</affiliations>
</json:item>
</author>
<subject><json:item><lang><json:string>eng</json:string>
</lang>
<value>Articles</value>
</json:item>
</subject>
<articleId><json:string>9.4.259</json:string>
</articleId>
<language><json:string>eng</json:string>
</language>
<originalGenre><json:string>research-article</json:string>
</originalGenre>
<abstract>Although concordances are in widespread use and have become the main output format of corpus analysis, they do little more than rearrange the selected data as a special kind of list. By yielding enough preceding and following context, however, concordances are usually sufficient for the purposes of classification and analysis. As items of high frequency have different senses, perform different functions, occur in differently constructed environments, and are thus used variably, classification is a major part of linguistic analysis. Up until now, however, it has. not been easy to store classificatory encodings alongside the concordance data, with a view to further exploitation of these encoded classifications. One solution is the importation of concordances into a database, where additional fields can then be created for mnemonic classificatory encodings, for further sorting on the basis of these encodings. This paper shows how this solution can be implemented in practice. It shows how concordances can come to be used in an ‘intelligent’ way as the basis of linguistic analysis; it also provides a practical tip for the use of the main software package for the analysis of interacting variables: VARBRUL For its quantitative and statistical correlation of co-occuring variants of different internal or external variables, VARBRUL depends utterly on a tokens file of encodings about the behaviour of each item. This paper shows how this tokens file can now be created by copying the classificatory encodings directly from the database.</abstract>
<qualityIndicators><score>7.844</score>
<pdfVersion>1.2</pdfVersion>
<pdfPageSize>583 x 848 pts</pdfPageSize>
<refBibsNative>false</refBibsNative>
<keywordCount>1</keywordCount>
<abstractCharCount>1549</abstractCharCount>
<pdfWordCount>7813</pdfWordCount>
<pdfCharCount>42900</pdfCharCount>
<pdfPageCount>8</pdfPageCount>
<abstractWordCount>237</abstractWordCount>
</qualityIndicators>
<title>Corpus-Concordance-Database-VARBRUL'</title>
<genre><json:string>research-article</json:string>
</genre>
<host><volume>9</volume>
<publisherId><json:string>litlin</json:string>
</publisherId>
<pages><last>266</last>
<first>259</first>
</pages>
<issn><json:string>0268-1145</json:string>
</issn>
<issue>4</issue>
<genre><json:string>journal</json:string>
</genre>
<language><json:string>unknown</json:string>
</language>
<eissn><json:string>1477-4615</json:string>
</eissn>
<title>Literary and Linguistic Computing</title>
</host>
<categories><wos><json:string>LINGUISTICS</json:string>
<json:string>LITERATURE</json:string>
</wos>
</categories>
<publicationDate>1994</publicationDate>
<copyrightDate>1994</copyrightDate>
<doi><json:string>10.1093/llc/9.4.259</json:string>
</doi>
<id>BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB</id>
<score>0.11843338</score>
<fulltext><json:item><original>true</original>
<mimetype>application/pdf</mimetype>
<extension>pdf</extension>
<uri>https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/fulltext/pdf</uri>
</json:item>
<json:item><original>false</original>
<mimetype>application/zip</mimetype>
<extension>zip</extension>
<uri>https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/fulltext/zip</uri>
</json:item>
<istex:fulltextTEI uri="https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Corpus-Concordance-Database-VARBRUL'</title>
<respStmt xml:id="ISTEX-API" resp="Références bibliographiques récupérées via GROBID" name="ISTEX-API (INIST-CNRS)"></respStmt>
<respStmt xml:id="ISTEX-API" resp="Références bibliographiques récupérées via GROBID" name="ISTEX-API (INIST-CNRS)"></respStmt>
<respStmt><resp>Références bibliographiques récupérées via GROBID</resp>
<name resp="ISTEX-API">ISTEX-API (INIST-CNRS)</name>
</respStmt>
</titleStmt>
<publicationStmt><authority>ISTEX</authority>
<publisher>Oxford University Press</publisher>
<availability><p>OUP</p>
</availability>
<date>1994</date>
</publicationStmt>
<notesStmt><note>School of English, The Queen;s University of belfast, Belfast BT7 1NN, Northern Ireland.</note>
</notesStmt>
<sourceDesc><biblStruct type="inbook"><analytic><title level="a">Corpus-Concordance-Database-VARBRUL'</title>
<author><persName><forename type="first">JOHN M.</forename>
<surname>KIRK</surname>
</persName>
<affiliation>The Queen's University of Belfast, Northern Ireland</affiliation>
</author>
</analytic>
<monogr><title level="j">Literary and Linguistic Computing</title>
<idno type="pISSN">0268-1145</idno>
<idno type="eISSN">1477-4615</idno>
<imprint><publisher>Oxford University Press</publisher>
<date type="published" when="1994"></date>
<biblScope unit="volume">9</biblScope>
<biblScope unit="issue">4</biblScope>
<biblScope unit="page" from="259">259</biblScope>
<biblScope unit="page" to="266">266</biblScope>
</imprint>
</monogr>
<idno type="istex">BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB</idno>
<idno type="DOI">10.1093/llc/9.4.259</idno>
<idno type="ArticleID">9.4.259</idno>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><creation><date>1994</date>
</creation>
<langUsage><language ident="en">en</language>
</langUsage>
<abstract><p>Although concordances are in widespread use and have become the main output format of corpus analysis, they do little more than rearrange the selected data as a special kind of list. By yielding enough preceding and following context, however, concordances are usually sufficient for the purposes of classification and analysis. As items of high frequency have different senses, perform different functions, occur in differently constructed environments, and are thus used variably, classification is a major part of linguistic analysis. Up until now, however, it has. not been easy to store classificatory encodings alongside the concordance data, with a view to further exploitation of these encoded classifications. One solution is the importation of concordances into a database, where additional fields can then be created for mnemonic classificatory encodings, for further sorting on the basis of these encodings. This paper shows how this solution can be implemented in practice. It shows how concordances can come to be used in an ‘intelligent’ way as the basis of linguistic analysis; it also provides a practical tip for the use of the main software package for the analysis of interacting variables: VARBRUL For its quantitative and statistical correlation of co-occuring variants of different internal or external variables, VARBRUL depends utterly on a tokens file of encodings about the behaviour of each item. This paper shows how this tokens file can now be created by copying the classificatory encodings directly from the database.</p>
</abstract>
<textClass><keywords scheme="keyword"><list><item><term>Articles</term>
</item>
</list>
</keywords>
</textClass>
</profileDesc>
<revisionDesc><change when="1994">Published</change>
<change xml:id="refBibs-istex" who="#ISTEX-API" when="2016-3-15">References added</change>
<change xml:id="refBibs-istex" who="#ISTEX-API" when="2016-3-21">References added</change>
<change xml:id="refBibs-istex" who="#ISTEX-API" when="2016-07-27">References added</change>
</revisionDesc>
</teiHeader>
</istex:fulltextTEI>
<json:item><original>false</original>
<mimetype>text/plain</mimetype>
<extension>txt</extension>
<uri>https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/fulltext/txt</uri>
</json:item>
</fulltext>
<metadata><istex:metadataXml wicri:clean="corpus oup" wicri:toSee="no header"><istex:docType PUBLIC="-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" URI="journalpublishing.dtd" name="istex:docType"></istex:docType>
<istex:document><article article-type="research-article"><front><journal-meta><journal-id journal-id-type="hwp">litlin</journal-id>
<journal-id journal-id-type="publisher-id">litlin</journal-id>
<journal-id journal-id-type="pmc">litlin</journal-id>
<journal-title>Literary and Linguistic Computing</journal-title>
<issn pub-type="epub">1477-4615</issn>
<issn pub-type="ppub">0268-1145</issn>
<publisher><publisher-name>Oxford University Press</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="publisher-id">9.4.259</article-id>
<article-id pub-id-type="doi">10.1093/llc/9.4.259</article-id>
<article-categories><subj-group><subject>Articles</subject>
</subj-group>
</article-categories>
<title-group><article-title>Corpus-Concordance-Database-VARBRUL'</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>KIRK</surname>
<given-names>JOHN M.</given-names>
</name>
</contrib>
<aff><institution>The Queen's University of Belfast</institution>
<addr-line>Northern Ireland</addr-line>
</aff>
</contrib-group>
<author-notes><corresp>School of English, The Queen;s University of belfast, Belfast BT7 1NN, Northern Ireland.</corresp>
</author-notes>
<pub-date pub-type="ppub"><year>1994</year>
</pub-date>
<volume>9</volume>
<issue>4</issue>
<fpage>259</fpage>
<lpage>266</lpage>
<copyright-statement>© Oxford University Press</copyright-statement>
<copyright-year>1994</copyright-year>
<abstract><p>Although concordances are in widespread use and have become the main output format of corpus analysis, they do little more than rearrange the selected data as a special kind of list. By yielding enough preceding and following context, however, concordances are usually sufficient for the purposes of classification and analysis. As items of high frequency have different senses, perform different functions, occur in differently constructed environments, and are thus used variably, classification is a major part of linguistic analysis. Up until now, however, it has. not been easy to store classificatory encodings alongside the concordance data, with a view to further exploitation of these encoded classifications. One solution is the importation of concordances into a database, where additional fields can then be created for mnemonic classificatory encodings, for further sorting on the basis of these encodings. This paper shows how this solution can be implemented in practice. It shows how concordances can come to be used in an ‘intelligent’ way as the basis of linguistic analysis; it also provides a practical tip for the use of the main software package for the analysis of interacting variables: VARBRUL For its quantitative and statistical correlation of co-occuring variants of different internal or external variables, VARBRUL depends utterly on a tokens file of encodings about the behaviour of each item. This paper shows how this tokens file can now be created by copying the classificatory encodings directly from the database.</p>
</abstract>
</article-meta>
</front>
</article>
</istex:document>
</istex:metadataXml>
<mods version="3.6"><titleInfo><title>Corpus-Concordance-Database-VARBRUL'</title>
</titleInfo>
<titleInfo type="alternative" contentType="CDATA"><title>Corpus-Concordance-Database-VARBRUL'</title>
</titleInfo>
<name type="personal"><namePart type="given">JOHN M.</namePart>
<namePart type="family">KIRK</namePart>
<affiliation>The Queen's University of Belfast, Northern Ireland</affiliation>
</name>
<typeOfResource>text</typeOfResource>
<genre type="research-article" displayLabel="research-article"></genre>
<subject><topic>Articles</topic>
</subject>
<originInfo><publisher>Oxford University Press</publisher>
<dateIssued encoding="w3cdtf">1994</dateIssued>
<copyrightDate encoding="w3cdtf">1994</copyrightDate>
</originInfo>
<language><languageTerm type="code" authority="iso639-2b">eng</languageTerm>
<languageTerm type="code" authority="rfc3066">en</languageTerm>
</language>
<physicalDescription><internetMediaType>text/html</internetMediaType>
</physicalDescription>
<abstract>Although concordances are in widespread use and have become the main output format of corpus analysis, they do little more than rearrange the selected data as a special kind of list. By yielding enough preceding and following context, however, concordances are usually sufficient for the purposes of classification and analysis. As items of high frequency have different senses, perform different functions, occur in differently constructed environments, and are thus used variably, classification is a major part of linguistic analysis. Up until now, however, it has. not been easy to store classificatory encodings alongside the concordance data, with a view to further exploitation of these encoded classifications. One solution is the importation of concordances into a database, where additional fields can then be created for mnemonic classificatory encodings, for further sorting on the basis of these encodings. This paper shows how this solution can be implemented in practice. It shows how concordances can come to be used in an ‘intelligent’ way as the basis of linguistic analysis; it also provides a practical tip for the use of the main software package for the analysis of interacting variables: VARBRUL For its quantitative and statistical correlation of co-occuring variants of different internal or external variables, VARBRUL depends utterly on a tokens file of encodings about the behaviour of each item. This paper shows how this tokens file can now be created by copying the classificatory encodings directly from the database.</abstract>
<note type="author-notes">School of English, The Queen;s University of belfast, Belfast BT7 1NN, Northern Ireland.</note>
<relatedItem type="host"><titleInfo><title>Literary and Linguistic Computing</title>
</titleInfo>
<genre type="journal">journal</genre>
<identifier type="ISSN">0268-1145</identifier>
<identifier type="eISSN">1477-4615</identifier>
<identifier type="PublisherID">litlin</identifier>
<identifier type="PublisherID-hwp">litlin</identifier>
<part><date>1994</date>
<detail type="volume"><caption>vol.</caption>
<number>9</number>
</detail>
<detail type="issue"><caption>no.</caption>
<number>4</number>
</detail>
<extent unit="pages"><start>259</start>
<end>266</end>
</extent>
</part>
</relatedItem>
<identifier type="istex">BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB</identifier>
<identifier type="DOI">10.1093/llc/9.4.259</identifier>
<identifier type="ArticleID">9.4.259</identifier>
<accessCondition type="use and reproduction" contentType="copyright">© Oxford University Press</accessCondition>
<recordInfo><recordContentSource>OUP</recordContentSource>
</recordInfo>
</mods>
</metadata>
<enrichments><istex:catWosTEI uri="https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/enrichments/catWos"><teiHeader><profileDesc><textClass><classCode scheme="WOS">LINGUISTICS</classCode>
<classCode scheme="WOS">LITERATURE</classCode>
</textClass>
</profileDesc>
</teiHeader>
</istex:catWosTEI>
<json:item><type>refBibs</type>
<uri>https://api.istex.fr/document/BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB/enrichments/refBibs</uri>
</json:item>
</enrichments>
<serie></serie>
</istex>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Ticri/explor/TeiVM2/Data/Istex/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000461 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 000461 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Ticri |area= TeiVM2 |flux= Istex |étape= Corpus |type= RBID |clé= ISTEX:BB91AA8C5A07C6FB65D07C0A1793123181B9E6FB |texte= Corpus-Concordance-Database-VARBRUL' }}
![]() | This area was generated with Dilib version V0.6.31. | ![]() |