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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> |
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<html xmlns="http://www.w3.org/1999/xhtml"> |
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<head> |
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /> |
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<title></title> |
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</head> |
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<body> |
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<div style="padding-left:25px;"> |
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<h1>SRCMF corpus: TIGERSearch web interface</h1> |
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<h2>Contents</h2> |
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<ul> |
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<li><a href="#interface">Using the TIGERSearch web interface</a></li> |
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<li><a href="#query">Writing a simple query</a></li> |
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<li><a href="#concordances">Exporting a concordance</a></li> |
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<li><a href="#tags">Tagset used</a></li> |
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<li><a href="#sample">Sample queries</a></li> |
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</ul> |
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<h2><a name="interface"></a>Using the TIGERSearch web interface</h2> |
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<h3>Writing a query and browsing the results</h3> |
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<p>In the TigerSearch tab, queries are entered in the top panel, and matching sentences |
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are shown in tree form in the bottom panel. A tutorial on TigerSearch queries may be |
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found in the section “<a href="#query">Writing a simple query</a>”.</p> |
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<ul> |
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<li>Type your query in the top panel (e.g. <tt>#pivot:[word = "Tristran"])</tt></li> |
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<li>Click on the ‘Search’ button at the bottom right of the panel.</li> |
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</ul> |
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<p>If the query is well-formed, and if there are matching results in the corpus, the |
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first tree in the forest will appear in the bottom panel.</p> |
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<p>The central bar gives the number of matches and the position of the sentence in the |
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corpus, in the form <i>sent: [sentence number] [match number] / [total matching |
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sentences].</i> Note that subgraph navigation is not yet implemented, and the |
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interface does <strong>not</strong> show the total number of matches, only the |
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number of matching sentences. You can navigate through the forest of matches using |
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the forward and back arrows on this bar. The ‘Export’ button displays the current |
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tree as an .SVG file in the browser, which can be saved and downloaded. The ‘Export |
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Concordance’ button allows matching sentences to be exported in <a |
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href="#concordances">concordance form</a>.</p> |
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<h3>Exporting the results</h3> |
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<p>To export the results of your query, click the ‘Export Concordance’ button. An export |
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window will appear, with the following options:</p> |
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<ul> |
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<li><p><strong>Type</strong></p> |
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<p>Three concordances are currently implemented:</p> |
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<ul> |
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<li>basic concordance</li> |
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<li>single word pivot concordance</li> |
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<li>pivot and block concordance</li> |
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</ul> |
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<p>It is important to note that these concordances use the names of TigerSearch |
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variables from the query to structure the concordance. <strong>No |
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concordance will be produced if your query does not contain a |
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<tt>#pivot</tt> variable.</strong> The pivot and block concordance |
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requires at least one additional <tt>#blockXX</tt> variable.</p> |
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<p>Further documentation for these concordances may be found in the section “<a |
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href="#concordances">Exporting a concordance</a>”.</p></li> |
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<li><p><strong>Context (number of words)</strong></p> |
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<p>Sets the size of the context preceding and following the pivot.</p></li> |
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<li><p><strong>Restore punctuation</strong></p> |
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<p>Adds punctuation from the BFM’s digitized edition to the exported |
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concordance. It will also restore words excluded from the TIGERSearch corpus |
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(e.g. lacunae, AOI in the <i>Chanson de Roland</i>).</p></li> |
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<li><p><strong>Properties to show in concordance</strong></p> |
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<p>Select which features of terminal and non-terminal nodes should be shown in |
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the concordance. This function is only active for the ‘pivot and block |
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concordance’.</p></li> |
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</ul> |
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<p>When you have filled in the form:</p> |
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<ul> |
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<li>Click the ‘OK’ button.</li> |
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</ul> |
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<p>After a short delay, a new tab will open in your browser, containing the concordance |
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in plain text tabular format (.csv).</p> |
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<ul> |
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<li>Save this file to disk using the ‘File > Save As...’ menu in your |
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browser.</li> |
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</ul> |
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<h3>Viewing the concordance</h3> |
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<p>To view and manipulate the concordance, you will need to use a spreadsheet |
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package.</p> |
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<ul> |
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<li>Open the spreadsheet application.</li> |
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<li>Select ‘File > Open...’ from the toolbar.</li> |
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<li>Ensure that the file list is showing either ‘All files’ or ‘CSV text |
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files’.</li> |
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<li>Select the saved .csv file.</li> |
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</ul> |
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<p>You will need to correctly configure your spreadsheet software to read the file. We |
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recommend using LibreOffice or OpenOffice Calc, which will prompt the user for |
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settings whenever a .csv file is opened. The following settings are required for the |
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import to function:</p> |
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<ul> |
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<li>Character set: Unicode (UTF-8);</li> |
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<li>Separated by Tab (ONLY);</li> |
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<li>Merge delimiters OFF;</li> |
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<li>Text delimiter: NONE (empty box)</li> |
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</ul> |
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<p>Troubleshooting likely problems:</p> |
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<ul> |
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<li>If accented characters do not appear correctly > check the character set is |
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UTF-8;</li> |
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<li>If some rows do not seem to have the correct number of columns > check that |
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Text Delimiter is set to nothing (the default is usually double quote, which |
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will cause an error where the text contains double quotes), merge delimiters is |
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OFF, and TAB is the only separator selected.</li> |
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<li>If zeros appear rather than punctuation (unlikely) > use the ‘Fields’ section |
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of the import window to set every column type to ‘Text’ rather than |
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‘Standard’.</li> |
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</ul> |
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<h2><a name="query"></a>Writing a simple query</h2> |
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<p>The following section will enable you to write simple TIGERSearch queries for the |
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SRCMF corpus. It is not comprehensive, and must be read in conjunction with:</p> |
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<ul> |
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<li>chapter III of the <a target="_blank" |
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href="http://www.ims.uni-stuttgart.de/projekte/TIGER/TIGERSearch/manual_html.html" |
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>TIGERSearch user’s guide</a></li> |
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</ul> |
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<h3>Nodes in the TS graph</h3> |
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<p>A TigerSearch graph is made up of two types of nodes: terminal and non-terminal |
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nodes. In the graph viewer, terminal nodes appear at the bottom of the graph, while |
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non-terminal nodes are represented by labelled white ovals, as shown in the example |
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<i>je puis dire</i>.</p> |
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<img src="images/jepuisdire.png" alt="Example TIGERSearch tree" /> |
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<p>Each node has a number of features (see section “<a href="#tags">Tagset used</a>”</p> |
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<h4>SRCMF: ‘split’ nodes</h4> |
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<p>In a true dependency graph, words form the only nodes.</p> |
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<p>In the TigerXML SRCMF corpus, each ‘word’ in the dependency structure is in fact |
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split between a terminal node (which contains the lexical form and the PoS tag of |
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the word itself) and a non-terminal node (which contains the syntactic features of |
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the structure headed by the word). The non-terminal node and the terminal node are |
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linked by an edge labelled ‘L’ (for lexical realization).</p> |
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<p>In the example tree, an ‘L’ edge links:</p> |
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<ul> |
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<li>the terminal node <i>puis</i> to the non-terminal node ‘Snt’: these nodes |
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represent the finite verb which heads the sentence;</li> |
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<li>the terminal node <i>je</i> to the non-terminal node ‘SjPer’: these nodes |
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represent the subject of the sentence <i>je</i>;</li> |
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<li>the terminal node <i>dire</i> to the non-terminal node ‘AuxA’: these nodes |
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represent the infinitive verb <i>dire</i>.</li> |
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</ul> |
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<p>A ‘D’ edge links the ‘Snt’ node to the non-terminal nodes ‘SjPer’ and ‘AuxA’: this |
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indicates that the subject <i>je</i> and the ‘auxiliated’ infinitive <i>dire</i> |
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depend on the main verb <i>puis</i>.</p> |
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<h4>SRCMF corpus node features</h4> |
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<p>The SRCMF corpus has the following node features:</p> |
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<p><i>Terminal nodes:</i></p> |
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<ul> |
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<li><tt>word</tt>: the word form</li> |
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<li><tt>pos</tt>: part-of-speech tag (Cattex)</li> |
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<li><tt>form</tt>: whether the text is verse or prose, and position of the word in |
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the line of verse.</li> |
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</ul> |
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<p><i>Non-terminal nodes:</i></p> |
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<ul> |
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<li><tt>cat</tt>: function of the structure headed by the node</li> |
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<li><tt>type</tt>: morpho-syntactic category of the node (VFin, VPar, VInf, NV)</li> |
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<li><tt>headpos</tt>: part-of-speech tag of the head word</li> |
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<li><tt>coord</tt>: set to ‘y’ if the structure forms part of a coordination</li> |
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<li><tt>dom</tt>: underscore-separated list of all functions dominated by the node |
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(e.g. for the ‘Snt’ node above ‘AuxA_SjPer’)</li> |
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</ul> |
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<p>For simple queries, we will focus mainly on the <tt>word</tt>, <tt>pos</tt> and |
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<tt>cat</tt> features.</p> |
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<h4>Defining the feature specifications of a node</h4> |
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<p>Node feature specifications are written between [square brackets] and take the |
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following form:</p> |
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<ul> |
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<li><tt>[feature operator "value"]</tt></li> |
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</ul> |
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<p>where <i>value</i> is a string or</p> |
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<ul> |
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<li><tt>[feature operator /value/]</tt></li> |
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</ul> |
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<p>where <i>value</i> is a regular expression. Permitted <i>operators</i> are ‘=’ |
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(equals) and ‘!=’ (does not equal). For example, the following expression identifies |
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all nodes where <tt>cat</tt> is "SjPer" (personal subject):</p> |
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<ul> |
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<li><tt>[cat = "SjPer"]</tt></li> |
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</ul> |
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<p>If we wish to include impersonal subjects (i.e. "SjPer" and "SjImp") we can use a |
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regular expression:</p> |
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<ul> |
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<li><tt>[cat = /Sj.*/]</tt></li> |
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</ul> |
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<p>We can identify all nodes which are <i>not</i> subjects:</p> |
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<ul> |
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<li><tt>[cat != /Sj.*/]</tt></li> |
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</ul> |
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<p>We may also the conjunction (&) operator within the square brackets to specify |
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several properties. For example, we can search for subordinate clause subjects by |
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requiring the subject to be headed by a finite verb (<tt>type</tt> is "VFin"):</p> |
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<ul> |
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<li><tt>[cat = /Sj.*/ & type = "VFin"]</tt></li> |
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</ul> |
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<h4>Assigning a variable name to a node</h4> |
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<p>A variable name may be assigned to the node definition. These are useful to refer to |
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the same node several times in a complex query and are also used to indicate the |
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pivot node to concordance scripts.</p> |
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<p>Variable definitions adopt the following syntax:</p> |
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<ul> |
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<li><tt>#name:[<definition>]</tt></li> |
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</ul> |
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<p>where <i>definition</i> is a feature specification as described above. Note that |
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variable names must begin with hash (#) and are separated from their definition by a |
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colon (:).</p> |
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<p>For example, we may to construct a concordance in which the subject forms the pivot. |
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We define the #pivot variable as follows:</p> |
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<ul> |
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<li><tt>#pivot:[cat = /Sj.*/]</tt></li> |
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</ul> |
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<h3>Node relations</h3> |
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<p>All but the most simple queries will require more than one node to be defined, and |
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will usually require the relationship between the nodes to be specified. </p> |
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<p>For example, suppose we wish to identify all subjects headed by the word |
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<i>Tristran</i>. First, we define the subject:</p> |
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<ul> |
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<li><tt>#subject:[cat = /Sj.*/]</tt></li> |
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</ul> |
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<p>Second, we define the word Tristran as a terminal node:</p> |
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<ul> |
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<li><tt>#tristran:[word = "Tristran"]</tt></li> |
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</ul> |
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<p>Finally, we must indicate the relationship between the nodes. The relationship |
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between a non-terminal node and the terminal node representing its lexical content |
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in the TigerSearch graph is one of direct dominance, labelled ‘L’ (lexical).</p> |
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<h4>Direct dominance</h4> |
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<p>In TigerSearch, direct dominance is expressed by using the operator ‘>’ with the |
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following syntax:</p> |
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<ul> |
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<li><tt>node >[label] node2</tt></li> |
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</ul> |
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<p>where <i>node</i> and <i>node2</i> are feature specifications or node variables, and |
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label (optional) is a string.</p> |
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<p>To identify subjects headed by the word <i>Tristran</i>, the relationship between |
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nodes #subject and #tristran is expressed as follows:</p> |
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<ul> |
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<li><tt>#subject >L #tristran</tt></li> |
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</ul> |
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<h4>Left corner dominance</h4> |
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<p>The ‘>@l’ operator specifies the leftmost terminal node dominated at any depth by a |
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non-terminal node. It has the following syntax:</p> |
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<ul> |
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<li><tt>node >@l tnode</tt></li> |
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</ul> |
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<p>where <i>node</i> and <i>tnode</i> are feature specifications or node variables, and |
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<i>tnode</i> is a terminal node.</p> |
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<p>For example, instead of searching for all subjects which are headed by the word |
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<i>Tristran</i>, we may wish to identify all subjects <strong>beginning</strong> |
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with the word <i>Tristran</i>. This relation would be written as follows:</p> |
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<ul> |
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<li><tt>#subject >@l #tristran</tt></li> |
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</ul> |
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<p>Note that there is also a right corner dominance operator ‘>@r’.</p> |
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<h4>Precedence</h4> |
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<p>The precedence operator ‘.*’ permits the user to specify the word order of two |
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terminal nodes with the following syntax:</p> |
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<ul> |
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<li><tt>tnode .* tnode2</tt></li> |
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</ul> |
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<p>where <i>tnode</i> and <i>tnode2</i> are feature specifications or node variables |
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representing terminal nodes.</p> |
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<p> For example, suppose we wish to identify all sentences in which the word Tristran |
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heads the subject and precedes the main clause verb.</p> |
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<p>We need to add two additional conditions to the query in the previous section. First, |
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we need to identify the terminal node containing the main verb of the sentence: i.e. |
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the lexical realization of the non-terminal node ‘Snt’:</p> |
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<ul> |
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<li><tt>#snt:[cat = "Snt"] >L #verb</tt></li> |
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</ul> |
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<p>You may have noticed that #verb has no feature specification. This is perfectly valid |
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in TigerSearch query syntax. In practice, we know that only one node can be linked |
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to #snt by an ‘L’ relation in the corpus. #Verb is thus defined by its relation to |
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#snt rather than by its features.</p> |
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<p>We then need to specify that the word Tristran precedes the verb:</p> |
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<ul> |
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<li><tt>#tristran .* #verb</tt></li> |
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</ul> |
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<p>Finally, we need to clarify that #subject is the the subject of #snt. Otherwise, we |
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risk finding subjects of a subordinate clause which happen to precede the main |
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clause verb:</p> |
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<ul> |
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<li><tt>#snt >D #subject</tt></li> |
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</ul> |
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<p>Putting it all together, the query is as follows:</p> |
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<ul> |
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<li><tt>#subject:[cat = /Sj.*/] >L #tristran:[word = "Tristran"] <br /> & |
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#snt:[cat = "Snt"] >L #verb <br /> & #tristran .* #verb <br /> & |
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#snt >D #subject</tt></li> |
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</ul> |
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<p>There is also a direct precedence operator, ‘.’, which specifies that the two |
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terminal nodes must be directly adjacent.</p> |
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<h4>Negation</h4> |
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<p>It is important to learn one (extremely frustrating) golden rule of Tiger query |
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syntax:</p> |
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<ul> |
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<li>you can negate a feature specification (e.g. <tt>[cat != "SjPer"]</tt>);</li> |
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<li>you can negate a relation between nodes (e.g. <tt>#subject !>L |
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#tristran</tt>)</li> |
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<li><strong>but you can’t negate the existence of a node!</strong></li> |
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</ul> |
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<p>In practice, this means that when we write:</p> |
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<ul> |
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<li><tt>#snt:[cat = "Snt"] !>D #subject:[cat = /Sj.*/]</tt></li> |
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</ul> |
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<p>we have <strong>not</strong> found all null subject main clauses. Instead, we have |
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asked for sentences (#snt) which contain a subject node (#subject) which is |
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<strong>not</strong> the subject of a sentence. TigerSearch will return all |
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sentences with subjects in a subordinate clause.</p> |
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<p>The SRCMF corpus provides a partial work-around for this problem by using the |
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<i>dom</i> feature. The <i>dom</i> feature of a non-terminal node lists the cat |
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features of all nodes linked to it by a ‘D’ edge in alphabetical order separated by |
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an underscore. For example, the ‘Snt’ node in the example tree has two dependants: |
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SjPer and AuxA. It therefore has a <i>dom</i> property ‘AuxA_SjPer’.</p> |
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<p>As a result, we can identify all main clauses without subjects by negating the |
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<i>dom</i> feature:</p> |
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<ul> |
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<li><tt>#snt:[cat = "Snt" & dom != /.*Sj.*/]</tt></li> |
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</ul> |
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<p>This will return all ‘Snt’ nodes whose <i>dom</i> property does not contain the |
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characters ‘Sj’: in other words, a main clause without an expressed subject.</p> |
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<h4>Syntactic variation</h4> |
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<p>TigerSearch syntax is quite flexible, and we may express queries in a number of ways. |
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For example, the query identifying all subjects headed by the word <i>Tristran</i> |
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may be expressed using three statements...</p> |
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<ul> |
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<li><tt>#subject:[cat = /Sj.*/] <br /> & #tristran:[word = "Tristran"] <br /> |
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& #subject >L #tristran</tt></li> |
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</ul> |
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<p>... or two statements, e.g.:</p> |
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<ul> |
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<li><tt>#subject:[cat = /Sj.*/] <br /> & #subject >L #tristran:[word = |
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"Tristran"]</tt></li> |
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</ul> |
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<p>... or one statement:</p> |
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<ul> |
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<li><tt>#subject:[cat = /Sj.*/] >L #tristran:[word = "Tristran"]</tt></li> |
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</ul> |
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<p>... or without variable names:</p> |
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<ul> |
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<li><tt>[cat = /Sj.*/] >L [word = "Tristran"]</tt></li> |
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</ul> |
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<p>Where multiple statements are used, the order of statements is irrelevant. |
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Confusingly for programmers, you may reference variables before assigning a value, |
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e.g.:</p> |
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<ul> |
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<li><tt>#subject >L #tristran & #tristran:[word = "Tristran"] & |
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#subject:[cat = /Sj.*/]</tt></li> |
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</ul> |
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<h2><a name="concordances"></a>Using concordances</h2> |
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<p>The SRCMF project has developed a number of concordances to present the results of |
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TigerSearch queries in tabular format. Three concordances are currently |
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implemented:</p> |
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<ul> |
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<li>basic concordance</li> |
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<li>single word pivot concordance</li> |
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<li>pivot and block concordance</li> |
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</ul> |
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<p>These concordances produce a text CSV file.</p> |
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<h3>Principles</h3> |
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<p>The concordances use the names of variables from the TigerSearch query to identify |
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the syntactic constituents which should form the focus of the table. All |
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concordances require a #pivot variable to be present in the query.</p> |
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<p>For example, the following query is correct in TigerSearch, but <strong>will |
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not</strong> produce a concordance:</p> |
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<ul> |
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<li><tt>[word = /Tristr?a[nm][sz]?/]</tt></li> |
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</ul> |
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<p>To produce a concordance, the query must identify a node as the #pivot, for |
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example:</p> |
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<ul> |
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<li><tt><strong>#pivot:</strong>[word = /Tristr?a[nm][sz]?/]</tt></li> |
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</ul> |
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<h3>Basic concordance</h3> |
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<p>The basic concordance has four columns:</p> |
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<ul> |
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<li>sentence ID</li> |
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<li>left context</li> |
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<li>pivot</li> |
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<li>right context</li> |
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</ul> |
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<p>The #pivot can be any node in the syntactic tree, either a single word or a larger |
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structure. Currently, only lexical information (not annotation) can be shown in the |
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basic concordance.</p> |
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<p>For example, we may wish to create a concordance of all the main clause subjects |
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containing the word ‘Tristran’:</p> |
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<ul> |
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<li><tt>#snt:[cat = "Snt"] >D #pivot:[cat = "SjPer"] & #pivot >* [word = |
387 |
/Tristr?a[nm][sz]?/]</tt></li> |
388 |
</ul> |
389 |
<p>Note that the #pivot variable is attached to the subject node (cat = "SjPer").</p> |
390 |
<p>Below is a selection of the results from the concordance:</p> |
391 |
<table border="1"> |
392 |
<tr> |
393 |
<th>ID</th> |
394 |
<th>contexte gauche</th> |
395 |
<th>pivot</th> |
396 |
<th>contexte droite</th> |
397 |
</tr> |
398 |
<tr> |
399 |
<td>beroul_pb:8_lb:234_1263227636.06</td> |
400 |
<td>di por averté Ce saciés vos de verité Atant s' en est Iseut tornee</td> |
401 |
<td>Tristran</td> |
402 |
<td>l' a plorant salüee Sor le perron de marbre bis Tristran s' apuie ce</td> |
403 |
</tr> |
404 |
<tr> |
405 |
<td>beroul_pb:13_lb:415_1264876249.02</td> |
406 |
<td># croiz Einz croiz parole fole et vaine Ma bone foi me fera saine Tristran |
407 |
[remest] a qui * mot poise </td> |
408 |
<td>Tristran tes niés </td> |
409 |
<td>vint soz cel pin Qui * est laienz en cel jardin Si me manda</td> |
410 |
</tr> |
411 |
<tr> |
412 |
<td>beroul_pb:134_lb:4365_1268928771.68</td> |
413 |
<td>moi le reçoive En sus l' atent s' espee tient Goudoïne autre voie tient</td> |
414 |
<td>Tristran [remest] a qui * mot poise</td> |
415 |
<td>Ist du * buison cela part toise Mais por noient quar cil s' esloigne</td> |
416 |
</tr> |
417 |
</table> |
418 |
<p>Note that the pivot may be one or more words.</p> |
419 |
<h3>What do the square brackets ([]), slashes (/), asterisks (*) and hashes (#) |
420 |
mean?</h3> |
421 |
<p>The third example in the above table contains [square brackets] in the pivot. These |
422 |
are used in all concordances to indicate <strong>words which occur between parts of |
423 |
a discontinuous syntactic constituent</strong>.</p> |
424 |
<p>The annotated subject in this sentence is <i>Tristran ... a qui mot poise</i>. The |
425 |
main verb of the sentence, <i>remest</i>, is not part of the subject, but occurs |
426 |
between its two parts. The verb <i>remest</i> is included in the pivot column, but |
427 |
surrounded by square brackets.</p> |
428 |
<p>This means that:</p> |
429 |
<ul> |
430 |
<li>the pivot column contains <strong>all parts</strong> of discontinuous |
431 |
pivots;</li> |
432 |
<li>reading the concordance from left to right will always give the original |
433 |
sentence.</li> |
434 |
</ul> |
435 |
<p>Slashes (/) indicate division between sentences in the syntactic annotation. These |
436 |
will not correspond to the editor’s division into sentences as shown in the |
437 |
punctuation.</p> |
438 |
<p>Asterisks (*) indicate that the preceding word has two syntactic functions (e.g. |
439 |
<i>qui</i> in <i>a qui mot poise</i> is both a relator and a subject). They may |
440 |
usually be ignored.</p> |
441 |
<p>Hashes (#) are related to the representation of coordination, and may always be |
442 |
ignored.</p> |
443 |
<h3>Single word pivot concordance</h3> |
444 |
<p>The single word pivot concordance has a variable number of columns, based on the |
445 |
following structure:</p> |
446 |
<ul> |
447 |
<li>ID</li> |
448 |
<li>Left context outside the SRCMF sentence containing the pivot</li> |
449 |
<li>Left context within the SRCMF sentence containing the pivot</li> |
450 |
<li>Pivot</li> |
451 |
<li>Structure headed by the pivot</li> |
452 |
<li>Function of the structure headed by the pivot</li> |
453 |
<li>Right context within the SRCMF sentence containing the pivot</li> |
454 |
<li>Right context outside the SRCMF sentence containing the pivot</li> |
455 |
</ul> |
456 |
<p>The single word pivot concordance is designed to give as much information as possible |
457 |
about a single word. For example, a concordance could be created around the word |
458 |
"Tristran":</p> |
459 |
<ul> |
460 |
<li><tt>#pivot:[word = /Tristr?a[nm][sz]?/]</tt></li> |
461 |
</ul> |
462 |
<p>Below is a selection of the results from the concordance (some columns are |
463 |
omitted):</p> |
464 |
<table border="1"> |
465 |
<tr> |
466 |
<th>Left context in sentence</th> |
467 |
<th>Pivot</th> |
468 |
<th>Pivot-headed structure</th> |
469 |
<th>Right context in sentence</th> |
470 |
</tr> |
471 |
<tr> |
472 |
<td>Sire</td> |
473 |
<td>Tristran</td> |
474 |
<td>Tristran</td> |
475 |
<td>por Deu le roi Si grant pechié avez de moi Qui * me mandez a itel ore</td> |
476 |
</tr> |
477 |
<tr> |
478 |
<td></td> |
479 |
<td>Tristran</td> |
480 |
<td>Tristran tes niés</td> |
481 |
<td>tes niés vint soz cel pin Qui * est laienz en cel jardin</td> |
482 |
</tr> |
483 |
<tr> |
484 |
<td># Que por Yseut que por</td> |
485 |
<td>Tristranz</td> |
486 |
<td>que por Tristranz</td> |
487 |
<td>Mervellose joie menoient</td> |
488 |
</tr> |
489 |
</table> |
490 |
<p>The ‘pivot-headed structure’ gives the noun phrase of which the word <i>Tristan</i> |
491 |
is head. In the second example, for instance, the word <i>Tristran</i> heads the |
492 |
structure <i>Tristan tes niés</i>.</p> |
493 |
<p>Note that words appearing in the ‘pivot-headed structure’ column are also found in |
494 |
the two context columns. The original sentence may be read across the columns left |
495 |
context — pivot — right context.</p> |
496 |
<h3>Pivot and block concordance</h3> |
497 |
<h4>Introduction</h4> |
498 |
<p>The pivot and block concordance is designed to highlight the position of certain |
499 |
constituents, called ‘blocks’ (e.g. the subject) with respect to a pivot (e.g. the |
500 |
verb). The resulting CSV files are complex, with a large number of columns, and are |
501 |
intended as the basis for more detailed analysis in spreadsheet software.</p> |
502 |
<p>The pivot and block concordances has the following basic structure:</p> |
503 |
<ul> |
504 |
<li>ID</li> |
505 |
<li>Left context outside the SRCMF sentence containing the pivot</li> |
506 |
<li>Left context within the SRCMF sentence containing the pivot</li> |
507 |
<li>Pre-pivot blocks</li> |
508 |
<li>Pivot</li> |
509 |
<li>Post-pivot blocks</li> |
510 |
<li>Right context within the SRCMF sentence containing the pivot</li> |
511 |
<li>Right context outside the SRCMF sentence containing the pivot</li> |
512 |
</ul> |
513 |
<p>As with the other concordances, TigerSearch queries must define a #pivot variable. |
514 |
However, any number of variables whose name begins ‘#block’ may be defined. At least |
515 |
one ‘#blockXX’ variable is required.</p> |
516 |
<p>For example, the following query will generate a pivot and block concordance to show |
517 |
the position of the subject (#block1) with respect to the finite verb (#pivot):</p> |
518 |
<ul> |
519 |
<li><tt>#snt:[cat = "Snt"] >D #block1:[cat = "SjPer"] & #snt >L |
520 |
#pivot</tt></li> |
521 |
</ul> |
522 |
<p>In essence, the central section of the resulting concordance will take the following |
523 |
form:</p> |
524 |
<table border="1"> |
525 |
<tr> |
526 |
<th>Left context</th> |
527 |
<th>Block</th> |
528 |
<th>Pivot</th> |
529 |
<th>Block</th> |
530 |
<th>Right context</th> |
531 |
</tr> |
532 |
<tr> |
533 |
<td></td> |
534 |
<td>Li rois</td> |
535 |
<td>pense</td> |
536 |
<td></td> |
537 |
<td>que par folie Sire Tristran vos aie amé</td> |
538 |
</tr> |
539 |
<tr> |
540 |
<td>Si</td> |
541 |
<td></td> |
542 |
<td>voient</td> |
543 |
<td>il</td> |
544 |
<td># Deu et son reigne</td> |
545 |
</tr> |
546 |
</table> |
547 |
<p>Where the subject is pre-verbal, it appears in the block column to the left of the |
548 |
pivot. Where it is post-verbal, it appears in the block column to the right of the |
549 |
pivot.</p> |
550 |
<h4>Why are there square brackets ([]) and curly brackets ({}) in the concordance?</h4> |
551 |
<p>As with other concordances, square brackets denote <strong>words occurring between |
552 |
two parts of a discontinuous unit</strong>. The difference in this concordance |
553 |
is that blocks may be discontinuous, as well as the pivot.</p> |
554 |
<p>Curly brackets denote <strong>words which occur between the block and the |
555 |
pivot</strong> (or, in more complex examples, between two blocks).</p> |
556 |
<table border="1"> |
557 |
<tr> |
558 |
<th>Left context</th> |
559 |
<th>Block</th> |
560 |
<th>Pivot</th> |
561 |
<th>Block</th> |
562 |
<th>Right context</th> |
563 |
</tr> |
564 |
<tr> |
565 |
<td></td> |
566 |
<td>Vos {n'}</td> |
567 |
<td>entendez</td> |
568 |
<td></td> |
569 |
<td>pas la raison</td> |
570 |
</tr> |
571 |
<tr> |
572 |
<td>Dex qel pitié</td> |
573 |
<td></td> |
574 |
<td>Faisoit</td> |
575 |
<td>{a} {mainte} {gent} li chiens</td> |
576 |
<td></td> |
577 |
</tr> |
578 |
<tr> |
579 |
<td></td> |
580 |
<td>Ta parole [est] [tost] [entendue] Que li rois la roïne prent</td> |
581 |
<td>est</td> |
582 |
<td></td> |
583 |
<td>tost entendue Que li rois la roïne prent</td> |
584 |
</tr> |
585 |
<tr> |
586 |
<td></td> |
587 |
<td>Tuit [s'] [escrïent] la gent du * reigne {s'}</td> |
588 |
<td>escrïent</td> |
589 |
<td></td> |
590 |
<td>la gent du * reigne</td> |
591 |
</tr> |
592 |
</table> |
593 |
<p>In the table above, note the use of curly brackets in the first example to mark the |
594 |
negative adverb <i>n’</i>, which occurs between the subject-block <i>vos</i> and the |
595 |
verb-pivot <i>entendez</i>. In the second example, the prepositional phrase <i>a |
596 |
maintes gens</i> is marked with curly brackets, as it separates the verb-pivot |
597 |
<i>Faisoit</i> from the post-verbal subject-block <i>li chiens</i>.</p> |
598 |
<p>In the third example, a discontinuous subject <i>Ta parole ... que li rois la roïne |
599 |
prent</i> appears in a pre-verbal block. <strong>The pre- or post-verbal |
600 |
position of a block is determined by the position of its first word relative to |
601 |
the pivot</strong>. The words <i>est tost entendue</i>, which separate the two |
602 |
parts of the block, are marked with square brackets. </p> |
603 |
<p>In the fourth example, the word <i>s’</i> appears (i) in square brackets, between the |
604 |
two halves of a discontinuous subject-block and (ii) in curly brackets, between the |
605 |
first part of the discontinuous subject <i>tost</i> and the verb-pivot |
606 |
<i>escrïent</i>.</p> |
607 |
<h4>Why are there so many columns? I only asked for one block!</h4> |
608 |
<p>The pivot and block concordance shows <strong>only one result per pivot</strong>. |
609 |
Continuing to work with the same example, if a single verb-pivot has multiple |
610 |
subject-blocks (which is quite possible in cases of coordination), each subject |
611 |
occupies a separate column:</p> |
612 |
<table border="1"> |
613 |
<tr> |
614 |
<th>Block3</th> |
615 |
<th>Block2</th> |
616 |
<th>Block1</th> |
617 |
<th>Pivot</th> |
618 |
<th>Block</th> |
619 |
</tr> |
620 |
<tr> |
621 |
<td>Ne tor</td> |
622 |
<td>ne mur</td> |
623 |
<td>ne fort chastel {Ne} {me}</td> |
624 |
<td>tendra</td> |
625 |
<td></td> |
626 |
</tr> |
627 |
</table> |
628 |
<p>However, due to the way the number of columns is calculated, it is possible that some |
629 |
will be empty. These may be deleted in the spreadsheet software, if you wish.</p> |
630 |
<p>Note that the concordance will <strong>never</strong> represent the two halves of a |
631 |
<strong>single discontinuous</strong> block in separate columns. The following |
632 |
representation therefore indicates a coordination:</p> |
633 |
<table border="1"> |
634 |
<tr> |
635 |
<th>Left context</th> |
636 |
<th>Block</th> |
637 |
<th>Pivot</th> |
638 |
<th>Block</th> |
639 |
<th>Right context</th> |
640 |
</tr> |
641 |
<tr> |
642 |
<td></td> |
643 |
<td>Tristran {en}</td> |
644 |
<td>bese</td> |
645 |
<td>{la} {roïne} {Et} ele</td> |
646 |
<td>lui par la saisine</td> |
647 |
</tr> |
648 |
</table> |
649 |
<p>The SRCMF of the sentence in this table identifies <strong>two coordinated |
650 |
subjects</strong> of the verb <i>bese</i>. One is pre-verbal (<i>Tristran</i>), |
651 |
one is post-verbal (<i>ele</i>); both occupy separate blocks.</p> |
652 |
<h3>Adding annotation information</h3> |
653 |
<p>When a concordance is launched from the TXM-web interface, you may specify which |
654 |
properties of terminal and non-terminal nodes you wish to see in the |
655 |
concordance.</p> |
656 |
<ul> |
657 |
<li>On the ‘Export Concordance’ form, use the drop-down lists of ‘Non-terminal |
658 |
features’ and ‘Terminal Features’.</li> |
659 |
<li>Select the features of terminal and non-terminal nodes that you wish to show in |
660 |
the concordance from the two drop-down lists.</li> |
661 |
<li>Click ‘OK’.</li> |
662 |
</ul> |
663 |
<p>Each added property will be placed in a separate column next to the block or pivot. |
664 |
For example, if the ‘cat’ property is selected for non-terminal nodes, and the ‘pos’ |
665 |
property is selected for terminal nodes, the query above will produce the following |
666 |
concordance:</p> |
667 |
<table border="1"> |
668 |
<tr> |
669 |
<th>Left context</th> |
670 |
<th>Block</th> |
671 |
<th>Block Cat</th> |
672 |
<th>Pivot</th> |
673 |
<th>Pivot Pos</th> |
674 |
<th>Block</th> |
675 |
<th>Block Cat</th> |
676 |
<th>Right context</th> |
677 |
</tr> |
678 |
<tr> |
679 |
<td></td> |
680 |
<td>Li rois</td> |
681 |
<td>SjPer</td> |
682 |
<td>pense</td> |
683 |
<td>VERcjg</td> |
684 |
<td></td> |
685 |
<td></td> |
686 |
<td>que par folie Sire Tristran vos aie amé</td> |
687 |
</tr> |
688 |
<tr> |
689 |
<td>Si</td> |
690 |
<td></td> |
691 |
<td></td> |
692 |
<td>voient</td> |
693 |
<td>VERcjg</td> |
694 |
<td>il</td> |
695 |
<td>SjPer</td> |
696 |
<td># Deu et son reigne</td> |
697 |
</tr> |
698 |
</table> |
699 |
<h2><a name="tags"></a>Tagset</h2> |
700 |
<h3>Non-terminal nodes</h3> |
701 |
<p>Non-terminal nodes have the following properties and values:</p> |
702 |
<h4>cat</h4> |
703 |
<p>Gives the syntactic function of the element. For more details, please refer to the <a |
704 |
target="_blank" href="http://srcmf.org">SRCMF |
705 |
website</a>.</p> |
706 |
<ul> |
707 |
<li><a name="Apst"></a><strong>Apst</strong>: Vocative (fr. apostrophe)</li> |
708 |
<li><a name="AtObj"></a><strong>AtObj</strong>: Object attribute</li> |
709 |
<li><a name="AtRfc"></a><strong>AtRfc</strong>: Attribute of reflexive pronoun</li> |
710 |
<li><a name="AtSj"></a><strong>AtSj</strong>: Subject attribute</li> |
711 |
<li><a name="Aux"></a><strong>Aux</strong>: Auxiliated non-finite verb (neither |
712 |
passive nor active)</li> |
713 |
<li><a name="AuxA"></a><strong>AuxA</strong>: Auxiliated non-finite verb |
714 |
(active)</li> |
715 |
<li><a name="AuxP"></a><strong>AuxA</strong>: Auxiliated non-finite verb |
716 |
(passive)</li> |
717 |
<li><a name="Circ"></a><strong>Circ</strong>: Adjunct (fr. circonstant)</li> |
718 |
<li><a name="Cmpl"></a><strong>Cmpl</strong>: Complement</li> |
719 |
<li><a name="Coo"></a><strong>Coo</strong>: Coordination</li> |
720 |
<li><a name="GpCoo"></a><strong>GpCoo</strong>: Coordinated group (conjunct)</li> |
721 |
<li><a name="Insrt"></a><strong>Insrt</strong>: Inserted clause</li> |
722 |
<li><a name="Intj"></a><strong>Intj</strong>: Interjection</li> |
723 |
<li><a name="ModA"></a><strong>ModA</strong>: Modifier (attached)</li> |
724 |
<li><a name="ModD"></a><strong>ModD</strong>: Dislocated (detached) modifier</li> |
725 |
<li><a name="Ng"></a><strong>Ng</strong>: Negation</li> |
726 |
<li><a name="NgPrt"></a><strong>NgPrt</strong>: Negative particle (e.g. <i>pas</i>, |
727 |
<i>mie</i></li> |
728 |
<li><a name="nSnt"></a><strong>nSnt</strong>: Non-sentence</li> |
729 |
<li><a name="Obj"></a><strong>Obj</strong>: Object</li> |
730 |
<li><a name="RelC"></a><strong>RelC</strong>: Coordinated relator</li> |
731 |
<li><a name="RelNC"></a><strong>RelNC</strong>: Non-coordinating relator</li> |
732 |
<li><a name="Regim"></a><strong>Regim</strong>: Regime</li> |
733 |
<li><a name="Rfc"></a><strong>Rfc</strong>: Reflexive pronoun</li> |
734 |
<li><a name="Rfx"></a><strong>Rfx</strong>: Doubled reflexive pronoun (e.g. <i>nous |
735 |
... <strong>nous-mêmes</strong></i>)</li> |
736 |
<li><a name="SjImp"></a><strong>SjImp</strong>: Impersonal subject</li> |
737 |
<li><a name="SjPer"></a><strong>SjPer</strong>: Personal subject</li> |
738 |
<li><a name="Snt"></a><strong>Snt</strong>: Sentence</li> |
739 |
</ul> |
740 |
<h4>type</h4> |
741 |
<p>Gives the syntactic category of the head of the structure.</p> |
742 |
<ul> |
743 |
<li><a name="VFin"></a><strong>VFin</strong>: Finite verb form</li> |
744 |
<li><a name="VInf"></a><strong>VInf</strong>: Infinitive</li> |
745 |
<li><a name="VPar"></a><strong>VPar</strong>: Participle</li> |
746 |
<li><a name="nV"></a><strong>nV</strong>: Non-verbal</li> |
747 |
</ul> |
748 |
<h4>dom</h4> |
749 |
<p>A ‘dom’ property is added to each non-terminal node in the tree listing the functions |
750 |
of all its dependants and relators in alphabetical order, separated by underscores. |
751 |
For example, if a finite verb has a subject, object and two adjuncts, the property |
752 |
[dom = "Circ_Circ_Obj_SjPer"] will be added.</p> |
753 |
<p>This resolves to an extent the problem of ‘negative’ queries. Recall that it is |
754 |
impossible to query the non-existence of a node:</p> |
755 |
<ul> |
756 |
<li><tt>#clause:[type = "VFin"] !>D #suj:[cat = "SjPer"]</tt></li> |
757 |
</ul> |
758 |
<p>Contrary to appearances, this query DOES NOT mean ‘node #suj does not exist’: it |
759 |
means that the node #suj exists, but is not dependant on #clause.</p> |
760 |
<p>However, it is possible to find all finite verbs without a subject by using the dom |
761 |
property of the finite verb:</p> |
762 |
<ul> |
763 |
<li><tt>#clause:[type = "VFin" & dom != /.*SjPer.*/]</tt></li> |
764 |
</ul> |
765 |
<p>The query specifies that we wish to find a node #clause which is a finite verb and |
766 |
does not have the string ‘SjPer’ in the list of dependant nodes given by the dom |
767 |
property.</p> |
768 |
<h4>coord</h4> |
769 |
<p>A ‘coord’ property is added to each non-terminal node in the tree. If the node |
770 |
represents a coordinated structure, [coord = "y"].</p> |
771 |
<p>For example, in the sentence <i>Sade et douz est quanqu’est de li</i> (gcoin1: p. 3, |
772 |
l. 31), <i>sade</i> and <i>douz</i> are coordinated AtSj. The non-terminal nodes |
773 |
dominating the words <i>sade</i> and <i>douz</i> have the properties [cat = "AtSj" |
774 |
& coord="y"].</p> |
775 |
<p>The ‘coord’ property exists primarily to allow non-coordinated structures to be |
776 |
identified. In the original format, this is not possible, as it would require a |
777 |
query specifying the non-existence of a node [cat = "Coo"]. However, with the coord |
778 |
property, it is possible to restrict a query to non-coordinated structures only:</p> |
779 |
<ul> |
780 |
<li><tt>#suj:[cat = "SjPer" & coord != "y"]</tt></li> |
781 |
</ul> |
782 |
<h4>headpos</h4> |
783 |
<p>A ‘headpos’ property is added to each non-terminal node in the tree. If the text is |
784 |
correctly annotated at the deep level, each non-terminal node representing a |
785 |
structure should directly dominate at most one terminal node in the tree, the word |
786 |
representing the lexical content of the head of the structure. If this is the case, |
787 |
the ‘headpos’ property is equal to the ‘pos’ property of the dominated terminal |
788 |
node. Thus:</p> |
789 |
<ul> |
790 |
<li><tt>#node:[headpos = "NOMcom"]</tt></li> |
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</ul> |
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<p>is equivalent to:</p> |
793 |
<ul> |
794 |
<li><tt>#node >L #lexnode:[pos = "NOMcom"]</tt></li> |
795 |
</ul> |
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<p>The headpos property does not improve the usability of the corpus in TigerSearch, but |
797 |
is useful in producing concordances, providing a more detailed morpho-syntactic tag |
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for the head of a structure than the SRCMF ‘NV’ (non-verbal) type tag.</p> |
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<p>If the non-terminal node directly dominates more than one terminal node, the |
800 |
algorithm generating the headpos property makes an calculated guess as to which word |
801 |
is the head, and inserts the tag of this word as the ‘headpos’. For example, if a |
802 |
non-terminal node dominates a word with pos ‘NOMcom’ and a word with pos ‘DETdef’, |
803 |
the algorithm will guess that the noun is the head, and insert the headpos |
804 |
‘NOMcom?’.</p> |
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<p>Note that headpos values which have been ‘guessed’ are always suffixed by a question |
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mark (e.g. NOMcom?). There will be no guessed headpos values in texts with full NP |
807 |
annotation.</p> |
808 |
<h3>Terminal nodes</h3> |
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<p>Terminal nodes have the following properties:</p> |
810 |
<h4>pos</h4> |
811 |
<p>Part-of-speech tag (Cattex). For more information, please refer to the <a |
812 |
target="_blank" href="http://bfm.ens-lyon.fr/article.php3?id_article=323">Cattex |
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documentation</a> on the <a target="_blank" href="http://bfm.ens-lyon.fr/">BFM website</a>.</p> |
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<h4>form</h4> |
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<p>Each word has a property “form”. For texts in prose, the value of the “form” tags is |
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always “prose”. For texts in verse, the form tag is:</p> |
817 |
<ul> |
818 |
<li>“vers_first” for the first word in a line;</li> |
819 |
<li>“vers_end” for the last word in a line;</li> |
820 |
<li>“vers” for other words.</li> |
821 |
</ul> |
822 |
<p>It is thus possible to formulate a TS query focusing on words at the beginning or end |
823 |
of a line of verse:</p> |
824 |
<ul> |
825 |
<li><tt>[word = "Tristran" & form = "vers_end"]</tt></li> |
826 |
</ul> |
827 |
<p>In <i>Aucassin and Nicolete</i>, the form tag correctly distinguishes the verse and |
828 |
prose sections of the text.</p> |
829 |
<h4>q</h4> |
830 |
<p>Each word has a property “q”. This is equal to ‘y’ when the word occurs as part of |
831 |
direct discourse, and ‘n’ when it does not. This annotation is automatically |
832 |
generated by the BFM team from the position of quote marks in the text.</p> |
833 |
<h2><a name="sample"></a>Sample queries</h2> |
834 |
<p> The following sample queries may be tested by copying and pasting into the query |
835 |
panel. </p> |
836 |
<p>Find all main clause verbs:<br /> |
837 |
<tt>[cat = "Snt"]</tt></p> |
838 |
<p>Find all structures introduced by a preposition:<br /> |
839 |
<tt>#n >R #relnc:[cat = "RelNC"]<br /> & #relnc >L [pos = /PRE.*/]</tt><br /> |
840 |
</p> |
841 |
<p>Find all post-verbal NP subjects:<br /> |
842 |
<tt>#verb:[type = "VFin"] >D #suj:[cat = "SjPer" & type="nV"]<br /> & #suj |
843 |
>L [pos = /NOM.*/] <br /> & #suj >@l #sword<br /> & #verb >L |
844 |
#vword<br /> & #vword .* #sword</tt></p> |
845 |
<p>Find indefinite subjects introduced by <q>qui</q>:<br /> |
846 |
<tt>[type = "VFin"] >D #suj:[cat = "SjPer"]<br /> & #suj >R #relnc:[cat = |
847 |
"RelNC"]<br /> & ( #relnc >L [word = /[QqKk]u?i/]<br /> | #relnc >~dupl |
848 |
[word = /[QqKk]u?i/] )</tt><br /></p> |
849 |
<p>Find sentences with coordinated subjects:<br /> |
850 |
<tt>#coo:[cat = "Coo"] >~coord #sj1:[cat = "SjPer"]<br /> & #coo >~coord |
851 |
#sj2:[cat = "SjPer"]<br /> & #sj1 $ #sj2</tt></p> |
852 |
<p>Find sentences with possible <q>gapping</q> of the finite verb (i.e. coordination of |
853 |
subject–predicate pairs):<br /> |
854 |
<tt>#gpcoo1:[cat = "GpCoo"] >~ #suj1:[cat = "SjPer"]<br /> & #gpcoo1 $.* |
855 |
#gpcoo2:[cat = "GpCoo"]<br /> & #gpcoo2 >~ #suj2:[cat = "SjPer"]<br /> & |
856 |
#gpcoo1 >~ #pred1:[cat = /Cmpl|Obj|AtSj/]<br /> & #gpcoo2 >~ #pred2:[cat = |
857 |
/Cmpl|Obj|AtSj/]<br /></tt> |
858 |
</p> |
859 |
<h1> Useful links</h1> |
860 |
<ul> |
861 |
<li><a target="_blank" href="https://listes.cru.fr/wiki/srcmf/index">SRCMF wiki</a></li> |
862 |
<li><a target="_blank" href="http://srcmf.org">SRCMF website</a></li> |
863 |
<li><a |
864 |
target="_blank" href="http://www.ims.uni-stuttgart.de/projekte/TIGER/TIGERSearch/oldindex.shtml" |
865 |
>TIGERSearch website</a></li> |
866 |
<li><a target="_blank" href="http://bfm.ens-lyon.fr/">BFM website</a></li> |
867 |
<li><a target="_blank" href="http://textometrie.ens-lyon.fr/?lang=en">TXM website</a></li> |
868 |
</ul> |
869 |
</div> |
870 |
</body> |
871 |
</html> |