Answers.Body: <p>It depends on the complexity on your sentences. If you have a limited range, you could do simple pattern matching on part-of-speech tags. Put your sentence through a tagger (there are plenty of them around) and look for the first noun following a verb:</p>
  
  <pre><code>I       want an         apple
  Pronoun verb determiner noun
  </code></pre>
  
  <p>(I assume you mean the <strong>object</strong>, as the subject in that sentence would be <em>I</em>). Scan through the list until you hit a verb, then pick the next noun. This should work for most English sentences.</p>
  
  <p>It gets a bit more complicated if your nouns have additional words around them, for example <em>red apple</em> (where <em>red</em> is an adjective) or <em>bottle of beer</em> (where you have the pattern <code>noun OF noun</code>). So if you want to capture those fully, you might need a few more complex matching rules.</p>
  
  <p>Overall it should still be a lot easier than implementing a full-blown syntactic parser which creates a comprehensive structural analysis of your sentence, most of which you wouldn't need in the first place.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-02-11T23:45:16.653Z
Answers.Text: I'm trying to do something similar to this.  I would like to perform sentiment analysis, however I need to keep track of the subject, so I can be aware of what the sentiment applies to.   using SVO, to manually parse it might work, what would you reccomend?
Answers.UserDisplayName: johnny 5
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-02-12T12:05:46.030Z
Answers.Text: Depends how precise it has to be. You can get quite far with simple heuristics, but every percentage accuracy in precision beyond say, 70-80 percent,  requires a lot more effort.
Answers.UserDisplayName: Oliver Mason
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-02-12T17:27:16.940Z
Answers.Text: Thanks, I'm going to try a hybrid solution.  use AI to find the subject using a syntax parser, and then some list of rules to see if the subject from the previous sentence is the same
Answers.UserDisplayName: johnny 5
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-02-13T11:59:32.647Z
Answers.Text: That sounds like a good approach.
Answers.UserDisplayName: Oliver Mason
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-12-06T10:11:33.960Z
Answers.LastActivityDate: 2018-12-06T10:11:33.960Z
Answers.UserDisplayName: Oliver Mason
Body: <p>I often develop bots and I need to understand what some people are saying.</p>
  
  <p>Examples:<br>
  - I want an apple<br>
  - I want an a p p l e</p>
  
  <p>How do I find the object (<em>apple</em>)? I honestly don't know where to start looking. Is there an API that I can send the text to which returns the object? Or perhaps I should manually code something that analyses the grammar?</p>
  
Tags: <algorithm><natural-language-processing><ai-basics><getting-started>
Title: How to find the subject in a text?
UserDisplayName: Matheus Freitas
ThreadText: # How to find the subject in a text?
  
  (Asked by: username_0 on 2018-02-15)
  
  I often develop bots and I need to understand what some people are saying.
  
  Examples:  
  - I want an apple  
  - I want an a p p l e
  
  How do I find the object (*apple*)? I honestly don't know where to start looking. Is there an API that I can send the text to which returns the object? Or perhaps I should manually code something that analyses the grammar?
  
  **Tags:** algorithm, natural-language-processing, ai-basics, getting-started
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2018-12-06. Score: 1
  
  It depends on the complexity on your sentences. If you have a limited range, you could do simple pattern matching on part-of-speech tags. Put your sentence through a tagger (there are plenty of them around) and look for the first noun following a verb:
  I       want an         apple
  Pronoun verb determiner noun
  
  (I assume you mean the object, as the subject in that sentence would be I). Scan through the list until you hit a verb, then pick the next noun. This should work for most English sentences.
  It gets a bit more complicated if your nouns have additional words around them, for example red apple (where red is an adjective) or bottle of beer (where you have the pattern noun OF noun). So if you want to capture those fully, you might need a few more complex matching rules.
  Overall it should still be a lot easier than implementing a full-blown syntactic parser which creates a comprehensive structural analysis of your sentence, most of which you wouldn't need in the first place.
  
  > **Comments:**
  > **username_2**: I'm trying to do something similar to this.  I would like to perform sentiment analysis, however I need to keep track of the subject, so I can be aware of what the sentiment applies to.   using SVO, to manually parse it might work, what would you reccomend?  
  > **username_1**: Depends how precise it has to be. You can get quite far with simple heuristics, but every percentage accuracy in precision beyond say, 70-80 percent,  requires a lot more effort.  
  > **username_2**: Thanks, I'm going to try a hybrid solution.  use AI to find the subject using a syntax parser, and then some list of rules to see if the subject from the previous sentence is the same  
  > **username_1**: That sounds like a good approach.  
  
  ---
  
  