test_spacy_model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import spacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "output_dir='/Users/yanliang/arabicNer/Arabic-NER/ar_test_output/model-final'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading from /Users/yanliang/arabicNer/Arabic-NER/ar_test_output/model-final\n"
     ]
    }
   ],
   "source": [
    "print(\"Loading from\", output_dir)\n",
    "nlp = spacy.load(output_dir)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<spacy.lang.ar.Arabic at 0x10d928588>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nlp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for text, _ in TRAIN_DATA:\n",
    "    doc = nlp2(text)\n",
    "    print('Entities', [(ent.text, ent.label_) for ent in doc.ents])\n",
    "    print('Tokens', [(t.text, t.ent_type_, t.ent_iob) for t in doc])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data1=\"و نشر العدل من خلال قضاء مستقل\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "doc1=nlp(data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entities [('قضاء مستقل', 'GPE')]\n"
     ]
    }
   ],
   "source": [
    "print('Entities', [(ent.text, ent.label_) for ent in doc1.ents])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tokens [('و', '', 2), ('نشر', '', 2), ('العدل', '', 2), ('من', '', 2), ('خلال', '', 2), ('قضاء', 'GPE', 3), ('مستقل', 'GPE', 1)]\n"
     ]
    }
   ],
   "source": [
    "print('Tokens', [(t.text, t.ent_type_, t.ent_iob) for t in doc1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data2="
   ]
  }
 ],
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