3. The Stanford Parser.ipynb

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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "3. The Stanford Parser"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The idea of this section is to analyze a sentence using the Stanford Parser (both for constituence and dependency) and display its results"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "a. Lexicalized Parsing"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pln_inco.syntax_trees\n",
      "import pln_inco.graphviz as gv\n",
      "from IPython.display import *\n",
      "import nltk.tree\n",
      "import pln_inco.stanford_parser\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 37
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I've prepared a little method to call the Stanford Parser (it assumes you have the parser installed and the CLASSPATH set, so you can call the parser from any directory), using (till now) the LexicalizedParser, trained with an english probabilistic context free grammar. Let's call it with a couple of sentences, and display their constituent trees. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "my_sentence='Bills on ports and immigration were submitted by Senator Brownback.' \n",
      "# You can change this sentence, if you don't like it!"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pr=pln_inco.stanford_parser.lexicalized_parser_parse([my_sentence],model='englishPCFG')\n",
      "print pr\n",
      "for p in pr:\n",
      "    t=nltk.tree.Tree.fromstring(p)\n",
      "    tree_dot=pln_inco.syntax_trees.tree_to_dot(t)\n",
      "\n",
      "    tree_png=Image(data=gv.generate(tree_dot,format='png'))\n",
      "    display_png(tree_png)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "['(ROOT\\n  (S\\n    (NP\\n      (NP (NNS Bills))\\n      (PP (IN on)\\n        (NP (NNS ports)\\n          (CC and)\\n          (NN immigration))))\\n    (VP (VBD were)\\n      (VP (VBN submitted)\\n        (PP (IN by)\\n          (NP (NNP Senator) (NNP Brownback.)))))))']\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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zZ478/f1Vt25dbd++XZUrVzadBMBJVa1aVd9++6169OihDh06KDQ0VJcvXzad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\n"
      }
     ],
     "prompt_number": 39
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "b. Dependency Parsing"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The Stanford parser can also return typed Dependencies, generated from the constituent tree (an introduction in [this](http://nlp.stanford.edu/pubs/LREC06_dependencies.pdf) paper, further explained [here](http://nlp.stanford.edu/software/dependencies_manual.pdf)). I've added a new argument to the method, allowing to specify the output (the original, default, value is 'penn'). Now, using 'basicDependencies' as an options, it will return the [basicDependencies](http://nlp.stanford.edu/software/stanford-dependencies.shtml) tree, which we will later incorporate into NLTK (this is possible because each word has just one head)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pr=pln_inco.stanford_parser.lexicalized_parser_parse(\n",
      "[my_sentence],\n",
      "model='englishPCFG',output='basicDependencies')\n",
      "for p in pr:\n",
      "    print p,'\\n'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "nsubjpass(submitted-7, Bills-1)\n",
        "prep(Bills-1, on-2)\n",
        "pobj(on-2, ports-3)\n",
        "cc(ports-3, and-4)\n",
        "conj(ports-3, immigration-5)\n",
        "auxpass(submitted-7, were-6)\n",
        "root(ROOT-0, submitted-7)\n",
        "prep(submitted-7, by-8)\n",
        "nn(Brownback.-10, Senator-9)\n",
        "pobj(by-8, Brownback.-10) \n",
        "\n"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The only format that the dependencyGrammar module from NLTK accepts is [Malt-TAB](http://stp.lingfil.uu.se/~nivre/research/MaltXML.html), from the Malt-parser, equivalent to the coNLL format. I will try to create a method to convert from Stanford representation to Malt-TAB representation. I need two pieces of info I do not still have: the POS tags, and the missing words (punctuation symbols). I will call the parser again, just to obtain the POS tags and tokens (I should better use the Stanford POS Tagger, but it is easier to call the parser)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import nltk.tag\n",
      "tagged_sentences=pln_inco.stanford_parser.lexicalized_parser_tag(\n",
      "[my_sentence],model='englishPCFG')\n",
      "words_and_pos=[nltk.tag.str2tuple(t) for t in tagged_sentences[0].split()]\n",
      "print words_and_pos"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[('Bills', 'NNS'), ('on', 'IN'), ('ports', 'NNS'), ('and', 'CC'), ('immigration', 'NN'), ('were', 'VBD'), ('submitted', 'VBN'), ('by', 'IN'), ('Senator', 'NNP'), ('Brownback', 'NNP'), ('.', '.')]\n"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now I can build a Malt-tab specification on the dependencies generated by the parser, merged with words and pos-tags emergining for the pos-tagging process (I am sure that they are equally tokenized because I have used the same tool)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "malt_tab_rep=pln_inco.syntax_trees.stanford_dependency_to_malt_tab(pr[0],words_and_pos)\n",
      "print malt_tab_rep"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "['Bills', 'on', 'ports', 'and', 'immigration', 'were', 'submitted', 'by', 'Senator', 'Brownback', '.']\n",
        "['NNS', 'IN', 'NNS', 'CC', 'NN', 'VBD', 'VBN', 'IN', 'NNP', 'NNP', '.']\n",
        "Bills\tNNS\t7\tnsubjpass\n",
        "on\tIN\t1\tprep\n",
        "ports\tNNS\t2\tpobj\n",
        "and\tCC\t3\tcc\n",
        "immigration\tNN\t3\tconj\n",
        "were\tVBD\t7\tauxpass\n",
        "submitted\tVBN\t0\troot\n",
        "by\tIN\t7\tprep\n",
        "Senator\tNNP\t10\tnn\n",
        "Brownback\tNNP\t8\tpobj\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We now can create a NLTK representation, as we did in the previous section:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dg = nltk.dependencygraph.DependencyGraph(malt_tab_rep)  \n",
      "print dg.tree().pprint()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(submitted\n",
        "  (Bills (on (ports and immigration)))\n",
        "  were\n",
        "  (by (Brownback Senator)))\n"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And, of course, display it!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dep_tree=pln_inco.syntax_trees.dependency_to_dot(dg)\n",
      "tree_png=Image(data=gv.generate(dep_tree,format='png'))\n",
      "display_png(tree_png)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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LFmHEiBGwt7cXyt588024uLjUdHh65Y033oChoSGOHz+Oc+fOYeHChTh06BBe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      }
     ],
     "prompt_number": 44
    }
   ],
   "metadata": {}
  }
 ]
}