{"id":1727,"date":"2019-09-15T09:29:57","date_gmt":"2019-09-15T03:59:57","guid":{"rendered":"https:\/\/www.rangakrish.com\/?p=1727"},"modified":"2019-09-15T20:55:13","modified_gmt":"2019-09-15T15:25:13","slug":"exploring-word-patterns","status":"publish","type":"post","link":"https:\/\/www.rangakrish.com\/index.php\/2019\/09\/15\/exploring-word-patterns\/","title":{"rendered":"Exploring Word Patterns"},"content":{"rendered":"

Working with word patterns can be an exciting (and challenging) creative activity. Such patterns come into picture while playing word games, solving word puzzles or even writing poetry. It is precisely to facilitate such tasks that I am building my “iLexicon”<\/strong><\/em> system.\u00a0<\/span><\/p>\n

One popular word game goes like this: The first player utters a word, and the next player is expected to say a word that starts with the ending syllable of the previous word. For example, if the first word is “Happy”<\/strong><\/em>, an acceptable next word is “Pylon”<\/strong><\/em>. And what can follow “Pylon”<\/strong><\/em>? The words “Loner”<\/strong><\/em>, “Longer”<\/strong><\/em>, “Longevity”<\/strong><\/em>, etc. are all OK.<\/p>\n

Let me show you how such word pairs can be generated using “iLexicon”<\/strong><\/em>. Look at the Prolog<\/strong><\/em> code below:<\/p>\n

\"Prolog<\/a>
Prolog Predicates for Word Pair Generation<\/strong><\/figcaption><\/figure>\n

There are 4 predicates. The predicate “get_noun_verb(N, V)”<\/strong><\/em> succeeds by binding “N”<\/strong><\/em> to a random noun and binding “V”<\/strong><\/em> to a verb that starts with the ending syllable of “N”<\/strong><\/em>. Similarly, the predicate “get_verb_noun(V, N)”<\/strong><\/em> succeeds by binding “V”<\/strong><\/em> to a random verb and binding “N”<\/strong><\/em> to a noun that starts with the ending syllable of “V”<\/strong><\/em>. I hope you can guess the functionality of the other two predicates “get_noun_noun(N1, N2)”<\/strong><\/em> and “get_verb_verb(V1, V2)”<\/strong><\/em>. I chose the categories “verb”<\/strong><\/em> and “noun”<\/strong><\/em> because they are quite common, but we can do this for other word categories too.<\/p>\n

Here is the sample output for <Noun, Verb><\/strong><\/em> pairs:<\/p>\n

\"<Noun,<\/a>
<Noun, Verb> Word Pairs<\/strong><\/figcaption><\/figure>\n

In the above example, “martyr”<\/strong><\/em> follows “grammar”<\/strong><\/em>, “sense”<\/strong><\/em> follows “nonsense”<\/strong><\/em>, “ball”<\/strong><\/em> follows “baseball”<\/strong><\/em> and “bitters”<\/strong><\/em> follows “rabbit”<\/strong><\/em>. All valid as per our rule, right?<\/p>\n

What follows are <Noun, Noun><\/strong><\/em> pairs:<\/p>\n

\"<Noun,<\/a>
<Noun, Noun> Word Pairs<\/strong><\/figcaption><\/figure>\n

In the above case, both the words are nouns. You can confirm that they are well-formed as per our rules.<\/p>\n

Next, some <Verb, Noun><\/strong><\/em> pairs:<\/p>\n

\"<Verb,<\/a>
<Verb, Noun> Word Pairs<\/strong><\/figcaption><\/figure>\n

Finally, <Verb, Verb><\/strong><\/em> pairs:<\/p>\n

\"<Verb,<\/a>
<Verb, Verb> Word Pairs<\/strong><\/figcaption><\/figure>\n

As I mentioned earlier, it is possible to generate such pairs between other word categories too, for example <Noun, Adjective><\/strong><\/em>, <Verb, Adverb><\/strong><\/em> and so on. Fortunately because of the huge collection of words and phrases contained in “iLexicon”<\/strong><\/em>, many such challenging problems can be solved.<\/p>\n

Hope you liked this discussion. I will take up other interesting patterns in future articles.<\/p>\n

Have a nice weekend!<\/p>\n","protected":false},"excerpt":{"rendered":"

Working with word patterns can be an exciting (and challenging) creative activity. Such patterns come into picture while playing word games, solving word puzzles or even writing poetry. It is precisely to facilitate such tasks that I am building my “iLexicon” system.\u00a0 One popular word game goes like this: The first player utters a word, […]<\/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_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[107,17,147],"tags":[130,134],"class_list":["post-1727","post","type-post","status-publish","format-standard","hentry","category-natural-language-processing","category-programming","category-prolog","tag-ilexicon","tag-word-patterns"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p9OLnF-rR","jetpack-related-posts":[{"id":2366,"url":"https:\/\/www.rangakrish.com\/index.php\/2021\/03\/28\/implementing-ilexicon-using-litedb\/","url_meta":{"origin":1727,"position":0},"title":"Implementing iLexicon using LiteDB","author":"admin","date":"March 28, 2021","format":false,"excerpt":"iLexicon is an \"intelligent\" dictionary that can be used to build Natural Language applications. I have two implementations, one in Lisp and another in Prolog. Both implementations are memory-based, in order to speed up performance. I have written several articles referencing it, for example see this. \u00a0 LiteDB is a\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":"Sample Commands","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/03\/Session1.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":2315,"url":"https:\/\/www.rangakrish.com\/index.php\/2021\/02\/14\/litedb-a-nosql-database-for-net\/","url_meta":{"origin":1727,"position":1},"title":"LiteDB: A NoSQL Database for .NET","author":"admin","date":"February 14, 2021","format":false,"excerpt":"I have been looking around for a compact embedded NoSQL database library for .NET, to use as the back-end of my \"iLexicon\" system. \"iLexicon\" is written in Lisp and Prolog (I have written a few articles\u00a0on it before). At present, the entire dictionary component (containing over 300,000 word entries) is\u2026","rel":"","context":"In "Programming"","block_context":{"text":"Programming","link":"https:\/\/www.rangakrish.com\/index.php\/category\/programming\/"},"img":{"alt_text":"Using Package Manager to Install LiteDB","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/02\/Package-Manager-300x98.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/02\/Package-Manager-300x98.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/02\/Package-Manager-300x98.jpg?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":846,"url":"https:\/\/www.rangakrish.com\/index.php\/2018\/02\/11\/onomatopoeia-palindrome-and-semordnilap\/","url_meta":{"origin":1727,"position":2},"title":"Onomatopoeia, Palindrome and Semordnilap","author":"admin","date":"February 11, 2018","format":false,"excerpt":"I had earlier\u00a0briefly talked about the Ilexicon project that I have been working on for some time now. The goal is to build an intelligent dictionary\u00a0that will come in handy while implementing NLP applications such as recognizers and generators. In today's post, I want to demonstrate some cool features available\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":863,"url":"https:\/\/www.rangakrish.com\/index.php\/2018\/03\/11\/kangaroo-words\/","url_meta":{"origin":1727,"position":3},"title":"Kangaroo Words","author":"admin","date":"March 11, 2018","format":false,"excerpt":"According to Wikipedia, \"A kangaroo word is a word that contains letters of another word, in order, with the same meaning. For example: the word 'masculine' contains the word 'male', which is a synonym of the first word; similarly, the word 'observe' contains its synonym 'see'.\" Interesting idea. The key\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1711,"url":"https:\/\/www.rangakrish.com\/index.php\/2019\/09\/01\/poetry-in-prolog-part-2\/","url_meta":{"origin":1727,"position":4},"title":"Poetry in Prolog: Part-2","author":"admin","date":"September 1, 2019","format":false,"excerpt":"In an earlier post, I showed how Prolog can be used to generate poetry, making use of my \"iLexicon\". I want to continue the discussion today by giving another example, this time based on the theme of sounds emitted by various animals and birds. As hinted in my previous articles,\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":"The DCG Grammar","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/09\/code.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/09\/code.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/09\/code.jpg?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":1410,"url":"https:\/\/www.rangakrish.com\/index.php\/2019\/01\/27\/generating-poetry-using-ilanggen\/","url_meta":{"origin":1727,"position":5},"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":[]}],"_links":{"self":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/1727","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=1727"}],"version-history":[{"count":0,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/1727\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/media?parent=1727"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/categories?post=1727"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/tags?post=1727"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}