{"id":1889,"date":"2020-02-16T10:24:09","date_gmt":"2020-02-16T04:54:09","guid":{"rendered":"https:\/\/www.rangakrish.com\/?p=1889"},"modified":"2020-02-16T10:28:44","modified_gmt":"2020-02-16T04:58:44","slug":"automatically-converting-active-voice-to-passive-voice-and-vice-versa","status":"publish","type":"post","link":"https:\/\/www.rangakrish.com\/index.php\/2020\/02\/16\/automatically-converting-active-voice-to-passive-voice-and-vice-versa\/","title":{"rendered":"Automatically Converting Active Voice to Passive Voice and Vice Versa"},"content":{"rendered":"

The iLexicon<\/strong><\/em> system can handle active\/passive<\/strong><\/em> voice conversion of fairly complex English sentences. I gave examples of the underlying verb conjugation<\/strong><\/em> mechanism in this article<\/strong><\/em><\/a>\u00a0and this one<\/strong><\/em><\/a>. Today, I am going to give examples of the conversion of complete sentences.<\/p>\n

Here is an example of active to passive voice conversion:<\/p>\n

\"Active<\/a>
Active To Passive Voice<\/strong><\/figcaption><\/figure>\n

The above is a snapshot of the interactive session in my Sicstus Prolog<\/strong><\/em><\/a>\u00a0IDE. You can see that the sentence “<\/strong>he drank milk”<\/strong><\/em> has been correctly converted to “<\/strong>milk was drunk by him”<\/strong><\/em>.<\/p>\n

Here are some more examples of active to passive voice conversion:<\/p>\n

\"Some<\/a>
Some More Examples<\/strong><\/figcaption><\/figure>\n

The last example is a special case that uses the preposition “to”<\/strong><\/em> instead of “by”<\/strong><\/em> in the passive voice.<\/p>\n

What about passive voice to active voice? The following is based on the earlier example:<\/p>\n

\"Passive<\/a>
Passive To Active Voice<\/strong><\/figcaption><\/figure>\n

It works as expected. Here are some more conversions:<\/p>\n

\"More<\/a>
More Examples – Passive To Active<\/strong><\/figcaption><\/figure>\n

Notice how the pronouns in the first example are suitably modified while changing the voice. The last example is a special case where the subject<\/strong><\/em> is missing. The word “someone”<\/strong><\/em> is introduced in this case when converting to active voice.<\/p>\n

Instead of converting from one voice to the other, we can give an active voice<\/strong><\/em> sentence and a passive voice<\/strong><\/em> sentence and check if they agree.<\/p>\n

\"Validating<\/a>
Validating Active\/Passive Sentence Pairs<\/strong><\/figcaption><\/figure>\n

Note that the system flags the second example as incorrect. The correct conversion of the active voice sentence “he drank the sweet milk<\/strong><\/em>” is “the sweet milk was drunk by him<\/strong><\/em>“.<\/p>\n

Here are more examples of this:<\/p>\n

\"More<\/a>
More Validation Examples<\/strong><\/figcaption><\/figure>\n

As you would have guessed, the first example shows incorrect conversion. The correct conversion is “the story book is being read by peter<\/strong><\/em>“.<\/p>\n

iLexicon’s<\/strong> <\/em>conversion engine first parses the given sentence to extract the Subject<\/strong><\/em>, Predicate<\/strong><\/em> and Object<\/strong><\/em>. Then it applies verb conjugation and active\/passive conversion rules, and finally emits the transformed structure. Below is a snapshot of the core logic (Prolog):<\/p>\n

\"The<\/a>
The Core Conversion Logic<\/strong><\/figcaption><\/figure>\n

It was challenging to work on this part but I thoroughly enjoyed it!<\/p>\n

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

The iLexicon system can handle active\/passive voice conversion of fairly complex English sentences. I gave examples of the underlying verb conjugation mechanism in this article\u00a0and this one. Today, I am going to give examples of the conversion of complete sentences. Here is an example of active to passive voice conversion: The above is a snapshot […]<\/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_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":[228,130,229,148],"class_list":["post-1889","post","type-post","status-publish","format-standard","hentry","category-natural-language-processing","category-programming","category-prolog","tag-active-voice","tag-ilexicon","tag-passive-voice","tag-prolog"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p9OLnF-ut","jetpack-related-posts":[{"id":1881,"url":"https:\/\/www.rangakrish.com\/index.php\/2020\/02\/02\/verb-conjugations-in-passive-voice\/","url_meta":{"origin":1889,"position":0},"title":"Verb Conjugations in Passive Voice","author":"admin","date":"February 2, 2020","format":false,"excerpt":"In my earlier article, I showed how the iLexicon system can generate verb conjugations based on quadruple. For the 16 tense forms discussed in that article, the verb conjugations were generated in \u201cactive\u201d voice.\u00a0 We all know that \u201ctransitive\" verbs can be expressed in both \u201cactive\u201d\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":"Passive Voice Conjugations - \"Drink\"","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2020\/02\/passive-voice3.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":2467,"url":"https:\/\/www.rangakrish.com\/index.php\/2021\/07\/04\/identifying-sentence-types-automatically\/","url_meta":{"origin":1889,"position":1},"title":"Identifying Sentence Types Automatically","author":"admin","date":"July 4, 2021","format":false,"excerpt":"Sentences in English can be classified into the following common types: - Simple sentence (\"I am drinking coffee\") - Compound sentence (\"He came home with his school friend and they had an enjoyable evening\") - Complex sentence (\"Whenever my dog barks, I give him some biscuit\") - Imperative sentence (\"Please\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":"Top-level Predicates","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/07\/code-300x233.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":2366,"url":"https:\/\/www.rangakrish.com\/index.php\/2021\/03\/28\/implementing-ilexicon-using-litedb\/","url_meta":{"origin":1889,"position":2},"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":2483,"url":"https:\/\/www.rangakrish.com\/index.php\/2021\/07\/18\/sentence-negation\/","url_meta":{"origin":1889,"position":3},"title":"Sentence Negation","author":"admin","date":"July 18, 2021","format":false,"excerpt":"In the last article, I talked about determining sentence types automatically. Another interesting task is to generate the \"negation\" of a given sentence. Example-1: Sentence => \"My teacher lives nearby\" Negation => \"My teacher does not live nearby\" Example-2: Sentence => \"She did not like that speech\" Negation => \"She\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":"Parse Tree","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/07\/parsetree-300x24.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/07\/parsetree-300x24.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2021\/07\/parsetree-300x24.jpg?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":1741,"url":"https:\/\/www.rangakrish.com\/index.php\/2019\/09\/29\/generating-verb-conjugations\/","url_meta":{"origin":1889,"position":4},"title":"Generating Verb Conjugations","author":"admin","date":"September 29, 2019","format":false,"excerpt":"We have been taught in school that English language has different \u201ctense\u201d forms. To help you quickly recollect, I am listing them in the table below (the verb 'sleep' is used as example): No. Tense Form Example Sentence (3rd Person Singular Pronoun) 1 Simple Present She sleeps 2 Simple Past\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":"Full Conjugation - Example3","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/09\/example3.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":1757,"url":"https:\/\/www.rangakrish.com\/index.php\/2019\/10\/13\/conjugating-phrasal-verbs\/","url_meta":{"origin":1889,"position":5},"title":"Conjugating Phrasal Verbs","author":"admin","date":"October 13, 2019","format":false,"excerpt":"In the last article, I showed how to generate verb conjugations in the \"iLexicon\" system. Today, let us see how this idea can be extended to English \"phrasal verbs\". According to Wikipedia: \"a phrasal verb is a phrase such as turn down or ran into which combines two or three\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":"Conjugation of \"Turn on\"","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2019\/10\/Example3.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\/1889","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=1889"}],"version-history":[{"count":0,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/1889\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/media?parent=1889"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/categories?post=1889"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/tags?post=1889"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}