PYWSD_BM.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import wordnet as wn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "showing info https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warming up PyWSD (takes ~10 secs)... took 13.580022811889648 secs.\n"
     ]
    }
   ],
   "source": [
    "from pywsd.lesk import simple_lesk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sent = 'I went to the bank to deposit my money'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ambiguous = 'bank'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "answer = simple_lesk(sent, ambiguous, pos='n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Synset('depository_financial_institution.n.01')\n"
     ]
    }
   ],
   "source": [
    "print(answer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a financial institution that accepts deposits and channels the money into lending activities\n"
     ]
    }
   ],
   "source": [
    "print(answer.definition())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pywsd import disambiguate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pywsd.similarity import max_similarity as maxsim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('I', None),\n",
       " ('went', Synset('run_low.v.01')),\n",
       " ('to', None),\n",
       " ('the', None),\n",
       " ('bank', Synset('depository_financial_institution.n.01')),\n",
       " ('to', None),\n",
       " ('deposit', Synset('deposit.v.02')),\n",
       " ('my', None),\n",
       " ('money', Synset('money.n.03'))]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "disambiguate('I went to the bank to deposit my money')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Synset('bank.n.01'),\n",
       " Synset('depository_financial_institution.n.01'),\n",
       " Synset('bank.n.03'),\n",
       " Synset('bank.n.04'),\n",
       " Synset('bank.n.05'),\n",
       " Synset('bank.n.06'),\n",
       " Synset('bank.n.07'),\n",
       " Synset('savings_bank.n.02'),\n",
       " Synset('bank.n.09'),\n",
       " Synset('bank.n.10'),\n",
       " Synset('bank.v.01'),\n",
       " Synset('bank.v.02'),\n",
       " Synset('bank.v.03'),\n",
       " Synset('bank.v.04'),\n",
       " Synset('bank.v.05'),\n",
       " Synset('deposit.v.02'),\n",
       " Synset('bank.v.07'),\n",
       " Synset('trust.v.01')]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wn.synsets('bank')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "kata = wn.lemmas(\"bank\", lang=\"zsm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Lemma('bank.n.10.bank'),\n",
       " Lemma('banking.n.02.bank'),\n",
       " Lemma('banking.n.01.bank'),\n",
       " Lemma('bank.v.05.bank'),\n",
       " Lemma('bank.v.03.bank'),\n",
       " Lemma('bank.n.09.bank'),\n",
       " Lemma('depository_financial_institution.n.01.bank'),\n",
       " Lemma('bank.n.03.bank'),\n",
       " Lemma('bank.n.05.bank')]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "kata = wn.synsets(\"bank\", lang=\"zsm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Synset('bank.n.10'),\n",
       " Synset('banking.n.02'),\n",
       " Synset('banking.n.01'),\n",
       " Synset('bank.v.05'),\n",
       " Synset('bank.v.03'),\n",
       " Synset('bank.n.09'),\n",
       " Synset('depository_financial_institution.n.01'),\n",
       " Synset('bank.n.03'),\n",
       " Synset('bank.n.05')]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from googletrans import Translator\n",
    "translator = Translator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A sister kite is stuck on the doorway.\n"
     ]
    }
   ],
   "source": [
    "sent = translator.translate('Layang-layang adik tersangkut pada ambang pintu.')\n",
    "print(sent.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('A', None),\n",
       " ('sister', Synset('sister.n.03')),\n",
       " ('kite', Synset('kite.n.04')),\n",
       " ('is', None),\n",
       " ('stuck', Synset('stick.v.15')),\n",
       " ('on', None),\n",
       " ('the', None),\n",
       " ('doorway', Synset('doorway.n.01'))]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "disambiguate('A sister kite is stuck on the doorway')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Synset('doorway.n.01')]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wn.synsets('doorway')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "kata = wn.synsets(\"ambang\", lang=\"zsm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Synset('sill.n.01'),\n",
       " Synset('sill.n.02'),\n",
       " Synset('threshold.n.01'),\n",
       " Synset('float.n.01')]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Najla', None),\n",
       " ('yang', Synset('yang.n.01')),\n",
       " ('pemalu', None),\n",
       " ('berasa', None),\n",
       " ('canggung', None),\n",
       " ('apabila', None),\n",
       " ('diminta', None),\n",
       " ('berucap', None)]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "disambiguate('Najla yang pemalu berasa canggung apabila diminta berucap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#bina python module for BM WSD yang mempunyai fungsi sama spt disambiguate() function drpd PyWSD\n",
    "\n",
    "Tasks:\n",
    "1. utilize Open Multilingual Wordnet (OMW)\n",
    "2. use Wordnet Bahasa (zsm)\n",
    "3. use Kamus Bahasa Melayu (DBP)??\n",
    "4. can handle multi-lingual/informal language? bm/english/chat...\n",
    "5. use deep learning technique - LSTM\n",
    "6. web-based app\n",
    "7. use Malaya/ own build tool (NLTK-BM)"
   ]
  }
 ],
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