{"id":637,"date":"2017-09-27T13:00:54","date_gmt":"2017-09-27T13:00:54","guid":{"rendered":"http:\/\/www.rangakrish.com\/?p=637"},"modified":"2017-09-27T13:02:12","modified_gmt":"2017-09-27T13:02:12","slug":"composition-of-grammars","status":"publish","type":"post","link":"https:\/\/www.rangakrish.com\/index.php\/2017\/09\/27\/composition-of-grammars\/","title":{"rendered":"Composition of Grammars"},"content":{"rendered":"

In the last post<\/a>, we saw how iLangGen<\/strong><\/em> text generation framework supports reuse of grammars through inheritance, akin to object-oriented languages. The good news is that we can achieve reuse through composition as well.<\/p>\n

The following is a simple grammar, nothing fancy to elaborate.<\/p>\n

\"Simple<\/a>
Simple Grammar<\/strong><\/figcaption><\/figure>\n

Here is the output when you traverse the grammar without AST.<\/p>\n

\"Output<\/a>
Output from Grammar<\/strong><\/figcaption><\/figure>\n

You can also obtain the AST as part of traversal.<\/p>\n

\"AST<\/a>
AST Output<\/strong><\/figcaption><\/figure>\n

The following grammar uses composition. You can see how the non-terminal y<\/strong><\/em> uses the end<\/strong><\/em> node of G1<\/strong><\/em>.<\/p>\n

\"Simple<\/a>
Composition of Grammars<\/strong><\/figcaption><\/figure>\n

This technique allows us to make use of certain nodes of a grammar without duplicating the logic. Here is the output from this grammar.<\/p>\n

\"Grammar<\/a>
Grammar Output<\/strong><\/figcaption><\/figure>\n

The following grammar, by embedding start@G1<\/strong><\/em>, uses the entire output of G1<\/strong><\/em> in its result.<\/p>\n

\"Embedding<\/a>
Embedding Entire Grammar<\/strong><\/figcaption><\/figure>\n

Here is the output.<\/p>\n

\"Grammar<\/a>
Grammar Output<\/strong><\/figcaption><\/figure>\n

Things can get slightly more interesting; we can combine inheritance and composition. The following grammar G1V<\/strong><\/em> is a variant of G1<\/strong><\/em> with the end<\/strong><\/em> node declared as virtual<\/strong><\/em>.<\/p>\n

\"Grammar<\/a>
Grammar with Virtual Node<\/strong><\/figcaption><\/figure>\n

The grammar Derived<\/strong><\/em> derives from G1V<\/strong><\/em>, defines a new node variant<\/strong><\/em> and overrides end<\/strong><\/em> node.<\/p>\n

\"Derived<\/a>
Derived Grammar<\/strong><\/figcaption><\/figure>\n

Here is the output generated by Derived<\/strong><\/em>. Note that variant<\/strong><\/em> node has no effect because it does not appear in the generation path. However, it could be used in other scenarios (see next example).<\/p>\n

\"Derived<\/a>
Derived Grammar Output<\/strong><\/figcaption><\/figure>\n

Let us now define grammar G4<\/strong><\/em>, which binds to (composition) variant<\/strong><\/em> of G4<\/strong><\/em>.<\/p>\n

\"Embedding<\/a>
Embedding Derived Grammar<\/strong><\/figcaption><\/figure>\n

When you run G4<\/strong><\/em>, you can see that it uses composition as well as inheritance!<\/p>\n

\"Grammar<\/a>
Grammar Output<\/strong><\/figcaption><\/figure>\n

In this way, i.e., through the use of inheritance and composition techniques, iLangGen<\/strong><\/em> facilitates building large grammar sets to model non-trivial text generation scenarios.<\/p>\n

In the coming posts, we will continue to explore other interesting features of iLangGen<\/strong><\/em>.<\/p>\n","protected":false},"excerpt":{"rendered":"

In the last post, we saw how iLangGen text generation framework supports reuse of grammars through inheritance, akin to object-oriented languages. The good news is that we can achieve reuse through composition as well. The following is a simple grammar, nothing fancy to elaborate. Here is the output when you traverse the grammar without AST. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[18,107],"tags":[109,108],"class_list":["post-637","post","type-post","status-publish","format-standard","hentry","category-lisp","category-natural-language-processing","tag-ilanggen","tag-text-generation"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p9OLnF-ah","jetpack-related-posts":[{"id":617,"url":"https:\/\/www.rangakrish.com\/index.php\/2017\/09\/13\/reuse-of-grammars-through-inheritance\/","url_meta":{"origin":637,"position":0},"title":"Reuse of Grammars Through Inheritance","author":"admin","date":"September 13, 2017","format":false,"excerpt":"We are familiar with the advantages of class inheritance in object-oriented languages such as C++, C#, Java, and Python. The ability to reuse functionality via inheritance allows us to express our software design optimally, without having to write redundant code. iLangGen encourages the reuse of grammars by supporting Grammar Inheritance,\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"Simple Grammar","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2017\/09\/image1.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2017\/09\/image1.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2017\/09\/image1.png?resize=525%2C300 1.5x"},"classes":[]},{"id":1410,"url":"https:\/\/www.rangakrish.com\/index.php\/2019\/01\/27\/generating-poetry-using-ilanggen\/","url_meta":{"origin":637,"position":1},"title":"Generating Poetry Using iLangGen","author":"admin","date":"January 27, 2019","format":false,"excerpt":"In an earlier article, I wrote about using iLangGen to generate natural language text. iLangGen is a powerful text generation library that I have been working on over the years. Today, I would like to show how we can use that library to generate \"poetry\". Be warned, however, that the\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"Sample Output 2","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/01\/Output2.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":575,"url":"https:\/\/www.rangakrish.com\/index.php\/2017\/08\/06\/text-generation-using-ilanggen-framework\/","url_meta":{"origin":637,"position":2},"title":"Text Generation Using iLangGen Framework","author":"admin","date":"August 6, 2017","format":false,"excerpt":"The two primary areas in Natural Language processing are Natural Language Understanding and Natural Language Generation. The former is concerned with processing and making sense of natural language text, whereas the latter is concerned with synthesizing text, possibly from some deep representation. Both are fascinating and at the same time,\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"iLangGen Grammar","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2017\/08\/Blog1.png?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2017\/08\/Blog1.png?resize=350%2C200 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2017\/08\/Blog1.png?resize=525%2C300 1.5x"},"classes":[]},{"id":2152,"url":"https:\/\/www.rangakrish.com\/index.php\/2020\/09\/28\/template-based-text-generation\/","url_meta":{"origin":637,"position":3},"title":"Template-Based Text Generation","author":"admin","date":"September 28, 2020","format":false,"excerpt":"I had written earlier about natural language generation\u00a0using my iLangGen framework. I used a \"template\" text file which was instantiated dynamically based on predefined \"grammars\" and external data. The sample application I show-cased demonstrated its utility and versatility. Today I would like to touch upon a few other \"pattern\" elements\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"Template File","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2020\/09\/Template-300x195.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2020\/09\/Template-300x195.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2020\/09\/Template-300x195.jpg?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":884,"url":"https:\/\/www.rangakrish.com\/index.php\/2018\/04\/08\/natural-language-generation\/","url_meta":{"origin":637,"position":4},"title":"Natural Language Generation","author":"admin","date":"April 8, 2018","format":false,"excerpt":"I had written a series of posts on my iLangGen framework last year. 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That implementation (in Lisp) made use of iLexicon, a large dictionary of English words, which I have been building over the years. I subsequently ported iLexicon to Prolog and it now\u2026","rel":"","context":"In "Natural Language Processing"","block_context":{"text":"Natural Language Processing","link":"https:\/\/www.rangakrish.com\/index.php\/category\/natural-language-processing\/"},"img":{"alt_text":"Generation Logic","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/08\/Code3.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/08\/Code3.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/08\/Code3.jpg?resize=525%2C300&ssl=1 1.5x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/637","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/comments?post=637"}],"version-history":[{"count":0,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/637\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/media?parent=637"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/categories?post=637"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/tags?post=637"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}