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    <p><strong>Constituents</strong></p> <p>It sounds like you want to identify the sentence's <a href="http://en.wikipedia.org/wiki/Constituent_%28linguistics%29" rel="noreferrer"><strong>constituents</strong></a>, which are groups of words that operate as a single unit according to the grammar of a language. </p> <p>In fact, when linguistics are trying to discover a language's grammar, they do it in part by looking at <a href="http://en.wikipedia.org/wiki/Constituent_%28linguistics%29#Movement" rel="noreferrer">movement</a>. As in your example, this is where a group of words can be moved to a different position in a sentence while still preserving the meaning of the sentence.</p> <p>Constituents can be individual words, phrases, or even larger groups such as whole clauses. Within a sentence, they have a nested hierarchical structure. For instance, the first example sentence you gave could be analyzed as:</p> <pre><code>(S (PP (IN On) (NP (NNP March) (CD 1))) (NP (PRP he)) (VP (VBD was) (VP (VBN born)))) </code></pre> <p>The whole sentence is made up of a <a href="http://en.wikipedia.org/wiki/Adpositional_phrase#Prepositional_phrases" rel="noreferrer">prepositional phrase</a>, followed by a <a href="http://en.wikipedia.org/wiki/Noun_phrase" rel="noreferrer">noun phrase</a>, and then a <a href="http://en.wikipedia.org/wiki/Verb_phrase" rel="noreferrer">verb phrase</a>. The prepositional phrase can be further decomposed into a unit consisting of the single word 'On' followed by a noun phrase. </p> <p><strong>Phrase Structure Parsers</strong></p> <p>To find constituents automatically, you will probably want to use a <strong>phrase structure parser</strong>. There are many such parses to choose from that are available as open source, including:</p> <ul> <li><a href="http://nlp.stanford.edu/software/lex-parser.shtml" rel="noreferrer">Stanford Parser</a> (Java)</li> <li><a href="http://berkeleyparser.googlecode.com/" rel="noreferrer">Berkeley Parser</a> (Java)</li> <li><a href="https://github.com/BLLIP/bllip-parser" rel="noreferrer">BLLIP (Charniak-Johnson) Parser</a> (C++)</li> <li><a href="http://www.cis.upenn.edu/~dbikel/software.html" rel="noreferrer">Bikel Parser</a> (this is a reimplemented and improved version of the Collins parser write in Java)</li> <li><a href="http://people.csail.mit.edu/mcollins/code.html" rel="noreferrer">Collins Parser</a> (C++)</li> <li><a href="http://opennlp.sf.net/" rel="noreferrer">OpenNLP Parser</a> (Java)</li> <li><a href="http://sharpnlp.codeplex.com/" rel="noreferrer">SharpNLP Parser</a> (C#)</li> </ul> <p>The Stanford and Berkeley parsers are probably the easiest to install and use. As seen in <a href="http://nlp.stanford.edu/pubs/lrecstanforddeps_final_final.pdf" rel="noreferrer">Cer et al. 2010</a>, the most accurate parsers are Berkeley and Charniak. The Bikel parser is slower and less accurate than the others. </p> <p><strong>Online Demo</strong></p> <p>There's an online demo for the Stanford parser <a href="http://nlp.stanford.edu:8080/parser/" rel="noreferrer">here</a>. I used the demo to produce the parse given above of your example sentence.</p> <p><strong>A Note About Deletion</strong></p> <p>Within each constituent, there will be a <a href="http://en.wikipedia.org/wiki/Head_%28linguistics%29" rel="noreferrer">head word</a>. For example, take the noun phrase:</p> <p><code>(NP (DT The) (JJ big) (JJ blue) (NN ball))</code> </p> <p>The head word here is the noun <code>ball</code>, and it is modified by the adjectives <code>big</code> and <code>blue</code>. If this noun phrase was embedded in a sentence, you could delete those modifiers and still have something that was consistent with, but less specific than, the meaning of the original sentence.</p> <p>Within noun phrases, you can generally delete the adjectives, nouns that are not the head, and nested prepositional phrases. </p> <p>Within verb phrases and complete clauses, things get more tricky since deleting material that servers as an argument to the verb can completely change the interpretation a sentence. For example, deleting <code>the book</code> from <code>He sold Jim the book</code> results in <strong><code>He sold Jim</code></strong>.</p>
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    1. POHow to get logical parts of a sentence with java?
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    1. COI just was looking at all these parsers and found a paper written by Daniel at http://nlp.stanford.edu/pubs/lrecstanforddeps_final_final.pdf
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    2. COYeah, that's actually my paper :)
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    3. COI was wondering about the Link Grammer Parser performance but I see in your paper you've covered it under the RelEx parser.
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