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"description": "=========\nCylleneus\n=========\n\n.. image:: https://img.shields.io/badge/cylleneus-next--gen%20corpus%20search%20for%20Greek%20and%20Latin-blue.svg\n :target: https://github.com/wmshort/cylleneus\n\n.. image:: https://img.shields.io/pypi/v/cylleneus.svg\n :target: https://pypi.python.org/pypi/cylleneus\n\n.. image:: https://travis-ci.org/wmshort/cylleneus.svg?branch=master\n :target: https://travis-ci.org/wmshort/cylleneus\n\n.. image:: https://readthedocs.org/projects/cylleneus/badge/?version=latest\n :target: https://cylleneus.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n\n* Free software: Apache Software License 2.0\n* Documentation: https://cylleneus.readthedocs.io.\n\n\nOverview\n--------\n\nCylleneus is a next-generation search engine for electronic corpora of Latin (and eventually Greek), which enables texts to be searched on the basis of their semantic and morpho-syntactic properties. This means that, for the first time, texts can be searched by the *meanings* of words as well as by the kinds of grammatical constructions they occur in. Semantic search takes advantage of the `Latin WordNet 2.0 `_ and is fully implemented, and thus is available for any annotated or plain-text corpus. Syntactic search functionality is still under development and is available for only certain structured corpora. However morphological searching and query filtering will work with any corpus.\n\n\nFeatures\n--------\n\n* Semantic search: find words based on their meanings in English, Italian, Spanish, or French\n* Syntactic search: finds words based on the kinds of grammatical constructions they appear in\n* Morphological search: find words, or filter the results of other queries, based on morphological properties\n* Fast: once a corpus is indexed, most query types produce results nearly instantaneously\n* Sophisticated: query types can be combined into complex search patterns\n* Extensible: indexing pipelines can be created for any corpus type\n* Free: completely open-source and redistributable\n\n\nInstallation\n------------\n\nClone this repository, navigate to the appropriate directory, and run the following command from your command line:\n\n``$ cd cylleneus``\n\n``$ python setup.py install``\n\nIt is also possible to ``pip install cylleneus``, but in this case you need to manage your own indexing.\n\n\nSetup\n-----\n\nThe Cylleneus engine requires texts to be indexed before they can be searched. For convenience and testing, this repository comes configured with three pre-indexed mini-corpora: some texts of Caesar from the LASLA corpus, Vergil's *Eclogues* from the Perseus Digital Library, and Seneca's *De Ira* and *De Beneficiis* from the Digital Latin Library.\n\nTo enable gloss-based searches, Cylleneus relies on the MultiWordNet. The setup process should install the latest version of the ``multiwordnet`` library, and also compile the necessary databases, but in case this step has been omitted you can do it manually. To do so, launch the Python REPL and enter the following commands.\n\n>>> from multiwordnet.db import compile\n>>> for language in ['common', 'english', 'latin', 'french', 'spanish', 'italian', 'hebrew']:\n... compile(language)\n\nTo test that everything is working properly, run the battery of query tests in ``tests/test_query_types.py`` over the packaged subcorpora.\n\n\nIndexing\n--------\n\nReady-made scripts are provided for indexing texts from the Perseus Digital Library (in JSON or TEI XML format), the LASLA corpus, the PHI5 corpus, and from plain-text sources (for instance, the Latin Library). To index a corpus (or part of one), the raw source should be placed in an appropriately named directory within ``/corpus//text/``. Then you can use any of the scripts in the ``scripts`` directory, modifying it for your own needs. The script for indexing texts from the DLL can be adapted to any plain-text source document. If you want to use texts from another corpus entirely, you will need to create an indexing pipeline tailored to the structure of that corpus. See the documentation for instructions.\n\nBasic indexing functionality is also provided through a command-line interface. ``$ cylleneus --help`` displays the complete list of available indexing commands.\n\nTo add a document or documents to a corpus, you must provide the original source files and indicate the correct path.\n\n``$ cylleneus index --corpus perseus # display the current index of corpus 'perseus'``\n\n``$ cylleneus add --corpus lasla --path \"/corpus/lasla/texts/Catullus_Catullus_Catul.BPN\" # for plaintext corpora you will also need to specify --author and --title, as this cannot be inferred from filenames or other metadata``\n\nIndexes should probably always be optimized, though this process can be slow if the corpus is large.\n\n``$ cylleneus optimize --corpus latin_library``\n\n\nSearching\n---------\n\nThe best way to search the available corpora (or to import new files individually) is to use the web app.\n\n``$ cd cylleneus``\n\n``$ cylleneus web``\n\nThen point your browser at http://127.0.0.1:5000. The web app can accommodate the full range of query types, and has functionality for viewing available corpora, importing new plain-text files, and exporting search results.\n\nA shell script, invoked by ``$ cylleneus shell``, is also available and provides a command-line interface to much of the same functionality.\n\nBoth the web app and the shell UI use the idea of a search collection, which is a grouping of texts from one or more corpora. This allows searches to be conducted across different corpus types, potentially filling gaps of text coverage. In the web app, click the ``Collection`` button to put together such a grouping before performing a search. In the shell UI, first select a corpus using ``corpus `` and then use ``select``. This commands takes a list of document numbers as its argument, i.e. ``\"[1,2...]\"``. Alternatively, ``select-all`` will add all the documents of the currently selected corpus to the search collection. Thus, e.g.:\n\n``cylleneus:~ $ corpus perseus; select-all; # selects the corpus and add all its documents to the search collection``\n\n``cylleneus:~ $ unselect \"[1]\" # remove document id 1 from the collection``\n\n``cylleneus:~ $ corpus lasla; select \"[1,2]\"' search |GEN.PL. # add documents from a different corpus and execute a different query``\n\nYou can display the list of documents within a corpus, with their id numbers, using the CLI.\n\n``$ cylleneus index --corpus perseus``\n\n\nQuery Types\n-----------\n\nCurrently, Cylleneus enables the following types of queries:\n\nWord-form queries\n~~~~~~~~~~~~~~~~~\n\n:Form: '...'\n:Example: 'virtutem'\n:Description: matches a literal string\n\nLemma-based queries\n~~~~~~~~~~~~~~~~~~~\n\n:Form: <...>\n:Example: \n:Description: matches any form of the specified lemma\n\nMore precision can be introduced by using LEMLAT URIs, along with morphological tagging. For example, in the Cylleneus shell ``search `` will match occurrences both of *dico*, *dicere* and of *dico*, *dicare*. To distinguish between them, you can use the relevant URIs: ```` (*dicare*) or ````. Alternatively, you can specify an appropriate morphological tag: ```` or ``.\n\nGloss-based queries\n~~~~~~~~~~~~~~~~~~~\n\n:Form: [...]\n:Example: [en?courage]\n:Description: matches any word with the same meaning as the specified gloss. Can be 'en', 'it', 'es', or 'fr'.\n:Example: [n#05595229]\n:Description: matches any word with the meaning defined by the specified synset offset ID\n\nDomain-based queries\n~~~~~~~~~~~~~~~~~~~~\n\n:Form: {...}\n:Example: {611}, {Anatomy}\n:Description: matches any word of any part of speech whose meaning falls within the specified domain. Cylleneus uses the Dewey Decimal Classification System as a general topic index.\n\nMorphology-based queries\n~~~~~~~~~~~~~~~~~~~~~~~~\n\n:Form: :...\n:Example: :ACC.SG.\n:Description: matches any word with the specified morphological properties, given in Leipzig notation. Annotations can be given as distinct query terms, or can be used as filters for lemma- or gloss-based queries. (For example, ``:PL.`` will match only plural forms of this word).\n\nMorphology-based filtering\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n:Form: <...>|...\n:Example: |GEN.SG.\n:Description: filters results for only genitive singular forms\n:Form: [...]:...\n:Example: [en?attack]\u00c2\u00a6VB.PL.\n:Description: filters results for only plural verb forms\n:Form: {...}:...\n:Example: {Anatomy}|ACC.\n:Description: filters results for only accusative forms\n\nLexical-relation queries\n~~~~~~~~~~~~~~~~~~~~~~~~\n\n:Form: \n:Example: \n:Description: matches any word with the specified lexical relation to the given lemma\n\nSemantic-relation queries\n~~~~~~~~~~~~~~~~~~~~~~~~~\n\n:Form: [?::...]\n:Example: [@::en?courage]\n:Description: matches any word with the specified semantic relation to the given gloss\n:Example: [@::n#05595229]\n:Description: matches any word with the specified semantic relation to the given synset\n\nSyntax-based queries\n~~~~~~~~~~~~~~~~~~~~\n\n:Form: /.../\n:Example: /ablative absolute/\n:Description: syntactical constructions (currently, only the LASLA corpus supports this)\n\nGloss-based searches enable searching by the meanings of words, and queries can be specified in English (en?), Italian (it?), Spanish (es?), or French (fr?). (NB. The vocabulary for Italian, Spanish, and French is significantly smaller than English).\nIt is also possible to search by synset ID number: this capability is exposed for future development of an interface where users can search for a specific sense. Normally, queries will be specified as English terms, which resolve to sets of synsets.\nQueries involving lexical and semantic relations depend on information available from the Latin Wordnet 2.0. As this project is on-going, rich relational information may be available only for a subset of vocabulary. However, as new information becomes available, search results should become more comprehensive and more accurate.\n\nTypes of lexical relations\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n======= ================\nCode Description\n======= ================\n``\\`` derives from (e.g., ``<\\::femina>`` would match any lemma derived from *femina*, namely, *femineus*)\n``/`` relates to (the converse of *derives from*)\n``+c`` composed of (e.g., ``<+c::cum>`` would match any lemma composed by *cum*)\n``-c`` composes (e.g., ``<-c::compono>`` would match lexical elements that compose *compono*, namely, *cum* and *pono*).\n``<`` participle (verbs only)\n======= ================\n\nTypes of semantic relations\n~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n======= ================\nCode Description\n======= ================\n``!`` antonym of\n``@`` hypernym of\n``~`` hyponym of\n``|`` nearest to\n``*`` entails\n``#m`` member of\n``#p`` part of\n``#s`` substance of\n``+r`` has role\n``%m`` has member\n``%p`` has part\n``%s`` has substance\n``-r`` is role of\n``>`` causes\n``^`` see also\n``$`` verb group\n``=`` attribute\n======= ================\n\nQuery types can be combined into complex adjacency or proximity searches. An adjacency search specifies a particular ordering of the query terms (typically, but not necessarily, sequential); a proximity search simply finds contexts where all the query terms occur, regardless of order.\nAdjacency searches must be enclosed with double quotes (\"...\"), optionally specifying a degree of 'slop', that is, the number of words that may intervene between matched terms, using '~' followed by the number of permissible intervening words.\n\nExamples\n~~~~~~~~\n\n``\"cui dono\"`` matches the literal string 'cui dono'\n\n``\"si quid \"`` matches 'si' followed by 'quid' followed by any form of *habeo*\n\n``\"cum :ABL.\"`` matches 'cum' followed by any word in the ablative causes\n\n``\"in |PL.\"`` matches 'in' followed by any plural form of *ager*\n\n``\" \"~2`` matches any form of *magnus* followed by any form of *animus*, including if separated by a single word\n\n`` `` matches any context including both any form of *honos* and any form of *virtus*\n\n\nTo Do\n-----\n\nIn no particular order...\n\n* Optimization\n* Integration with Scaife Viewer\n* Perseus CTS alignment for corpora with non-standard text annotations\n* implement high-order syntactic search for different annotation schemes\n* manually-curated WordNet-based semantic mark-up ('sembanks') for texts\n* Greek\n\n\nCredits\n-------\n\n\u00c2\u00a9 2019 William Michael Short. Based on the open-source Whoosh search engine by Matt Chaput. \n\n\n=======\nHistory\n=======\n\n0.0.3 (2019-07-30)\n------------------\n\n* General improvements to corpus management, indexing, searching and CL tools\n\n0.0.2 (2019-07-15)\n------------------\n\n* Improvements to indexing and searching\n\n0.0.1 (2019-06-15)\n------------------\n\n* Public release on GitHub.",
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