{"id":582,"date":"2017-07-19T14:10:53","date_gmt":"2017-07-19T14:10:53","guid":{"rendered":"http:\/\/uscictdialdev.wpenginepowered.com\/?page_id=582"},"modified":"2017-07-19T14:11:59","modified_gmt":"2017-07-19T14:11:59","slug":"berkeley-nlp-tools","status":"publish","type":"page","link":"https:\/\/dialport.ict.usc.edu\/index.php\/resources\/nlp-toolkits\/berkeley-nlp-tools\/","title":{"rendered":"Berkeley NLP Tools"},"content":{"rendered":"<p><a href=\"http:\/\/nlp.cs.berkeley.edu\/software.shtml\">About<\/a><\/p>\n<p>&nbsp;<\/p>\n<h4>Libraries<\/h4>\n<ul class=\"bulletless\">\n<li><a class=\"title_link\" href=\"https:\/\/github.com\/tberg12\/murphy\">Murphy<\/a>\u00a0is a library of learning algorithms for structured prediction.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Parsing<\/h4>\n<ul class=\"bulletless\">\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/code.google.com\/p\/berkeleyparser\/\">Berkeley Parser<\/a>\u00a0infers syntactic annotations. We have an\u00a0<a href=\"http:\/\/tomato.banatao.berkeley.edu:8080\/parser\/parser.html\">online demo<\/a>!<\/li>\n<li><a class=\"title_link\" href=\"http:\/\/www.github.com\/dlwh\/puck\/\">Puck<\/a>\u00a0is a lightning-fast version of the Berkeley Parser that uses GPUs.<\/li>\n<li><a class=\"title_link\" href=\"https:\/\/www.github.com\/dlwh\/epic\/\">Epic<\/a>\u00a0is a discriminative parser using many kinds of annotations.<\/li>\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/nlp.cs.berkeley.edu\/projects\/neuralcrf.shtml\">neural CRF parser<\/a>\u00a0effectively leverages distributed representations of words by scoring anchored rule productions with feedforward neural networks.<\/li>\n<li>The\u00a0<a class=\"title_link\" href=\"https:\/\/github.com\/jkkummerfeld\/berkeley-parser-analyser\">Berkeley Parser Analyser<\/a>\u00a0performs error analysis on parse trees.<\/li>\n<li>The\u00a0<a class=\"title_link\" href=\"https:\/\/github.com\/jkkummerfeld\/berkeley-ccg2pst\">Berkeley CCG to PST tool<\/a>\u00a0converts CCG Derivations into Penn Treebank style trees.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Coreference Resolution<\/h4>\n<ul class=\"bulletless\">\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/nlp.cs.berkeley.edu\/projects\/entity.shtml\">Berkeley Entity Resolution System<\/a>\u00a0jointly models and predicts named entity chunks, coreference, and entity links.<\/li>\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/nlp.cs.berkeley.edu\/projects\/coref.shtml\">Berkeley Coreference Resolution System<\/a>\u00a0is a high-performing English coreference resolution system.<\/li>\n<li>The\u00a0<a class=\"title_link\" href=\"https:\/\/github.com\/jkkummerfeld\/berkeley-coreference-analyser\">Berkeley Coreference Analyser<\/a>\u00a0performs error analysis on coreference resolution output.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Summarization<\/h4>\n<ul class=\"bulletless\">\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/nlp.cs.berkeley.edu\/projects\/summarizer.shtml\">Berkeley Document Summarizer<\/a>\u00a0is an extractive and compressive single-document summarization system learned on a large newswire corpus.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Historical Document Recognition<\/h4>\n<ul class=\"bulletless\">\n<li><a class=\"title_link\" href=\"https:\/\/github.com\/tberg12\/ocular.git\">Ocular<\/a>\u00a0is a state-of-the-art historical document recognition system.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Word Alignment<\/h4>\n<ul class=\"bulletless\">\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/code.google.com\/p\/berkeleyaligner\/\">Berkeley Aligner<\/a>\u00a0aligns the words in multilingual parallel texts.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Language Modeling<\/h4>\n<ul class=\"bulletless\">\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/code.google.com\/p\/berkeleylm\/\">Berkeley LM<\/a>\u00a0provides a library for storing large n-gram language models efficiently in memory.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Education<\/h4>\n<ul class=\"bulletless\">\n<li>The\u00a0<a class=\"title_link\" href=\"http:\/\/inst.eecs.berkeley.edu\/~cs188\/pacman\/home.html\">Pac-Man projects<\/a>\u00a0are a set of class projects that teach foundational AI concepts, such as informed state-space search, probabilistic inference, and reinforcement learning.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>About &nbsp; Libraries Murphy\u00a0is a library of learning algorithms for structured prediction. &nbsp; Parsing The\u00a0Berkeley Parser\u00a0infers syntactic annotations. We have an\u00a0online demo! Puck\u00a0is a lightning-fast version of the Berkeley Parser that uses GPUs. Epic\u00a0is a discriminative parser using many kinds of annotations. The\u00a0neural CRF parser\u00a0effectively leverages distributed representations of words by scoring anchored rule productions [&hellip;]<\/p>\n","protected":false},"author":18,"featured_media":0,"parent":410,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-582","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/pages\/582","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/comments?post=582"}],"version-history":[{"count":0,"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/pages\/582\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/pages\/410"}],"wp:attachment":[{"href":"https:\/\/dialport.ict.usc.edu\/index.php\/wp-json\/wp\/v2\/media?parent=582"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}