{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import SentSeg\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[['Hallo', 'was', 'gehe', 'denn', 'hier', 'so.']], [['Ich', 'habe', 'echt', 'keine', 'Ahnung', 'verdammt.']], [['I.', 'd.', 'R.', 'gibt', 'es', 'keine', 'Abschiebungen.']], [['Ende', 'd.', 'J.', 'wird', 'alles', 'problematisch.']], [['Sie', 'gingen', 'nach', 'Hause,', 'weil', 'es', 'in', 'Strömen', 'regnete.']], [['Heute', 'war', 'die', 'Straße', 'blau', 'angemalt,', 'damit', 'der', 'Marathon', 'funktionierte.']], [['Er', 'habe', 'es', 'sehr', 'schwer.']], [['Es', 'war', 'die', 'Hose', 'des', 'Gauners.']], [['Bliblablub.']], [['Sie', 'ist', 'nicht', 'schön', 'heute.']], [['Oleoleole.']], [['Mannoman.']], [['Er', 'ginge', 'nicht', 'schnell.']], [['Die', 'Hühner', 'lieben', 'sich', 'nicht.']]]\n" ] } ], "source": [ "sent_seg = SentSeg.SentSeg('de')\n", "\n", " \n", "sentences = sent_seg.ReadDoc2Sent('atest1')\n", "print(sentences)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "initializing the gs utils..\n", "loading spacy..\n", "done\n", "done\n", "loading the Stochastic Gradient models..\n", "done\n", "initializing the SGM..\n", "loading vectorizer..\n", "done\n", "loading the SGD model..\n", "done\n", "loading spacy..\n", "done\n", "done\n", "importing spacy..\n", "done\n", "importing german model..\n", "done\n" ] }, { "data": { "text/plain": [ "'done'" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sent_seg.LoadSentGlueSGDandGSUtils()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "creating array of comma or not..\n", "done\n" ] } ], "source": [ "sentences = sent_seg.CommaSentenceOrNot(sentences)\n", "print(sentences)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "sentences = sent_seg.GetUtteranceNumber(sentences)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "sentences = sent_seg.GetQuestionOrNot(sentences)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "importing spacy..\n", "done\n" ] } ], "source": [ "sentences1 = sent_seg.SplitSentencesIntoHauptNebenTuple(sentences)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['es', 'regnete', 'in Strömen']\n", "['deswegen', 'Sie', 'gingen', 'nach Hause']\n", "['Heute', 'war', 'blau', 'angemalt', 'die Straße']\n", "100\n", "['dann', 'funktionierte', 'der Marathon']\n" ] } ], "source": [ "outsentences = sent_seg.SplitCommatas(sentences1)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[['Hallo', 'was', 'gehe', 'denn', 'hier', 'so'], ['Ich', 'habe', 'echt', 'keine', 'Ahnung', 'verdammt'], ['I.', 'd.', 'R.', 'gibt', 'es', 'keine', 'Abschiebungen'], ['Ende', 'd.', 'J.', 'wird', 'alles', 'problematisch'], ['in', 'Strömen', 'regnete', 'e'], ['deswegen', 'gingen', 'Sie', 'nach', 'Haus'], ['angemalt', 'war', 'die', 'Straße', 'blau', 'Heut'], ['dann', 'der', 'Marathon', 'funktioniert'], ['Er', 'habe', 'es', 'sehr', 'schwer'], ['Es', 'war', 'die', 'Hose', 'des', 'Gauners'], ['Bliblablub'], ['Oleoleole'], ['Mannoman'], ['Er', 'ginge', 'nicht', 'schnell'], ['Der', 'Satz', 'davor', 'funktioniert', 'nicht', 'im', 'Modul', 'Konjunktsolve'], ['Weil', 'er', 'zu', 'viele', 'verben', 'hat']]\n" ] } ], "source": [ "print(outsentences)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "punctuations = []\n", "for n in range(len(outsentences)):\n", " punctuations.append('.')\n", " if outsentences[n][-1][-1] == '.':\n", " outsentences[n][-1] = outsentences[n][-1][:-1]" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "from oi import *\n", "oi = oi()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n", ".\n" ] }, { "data": { "text/plain": [ "'OK'" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "oi.PrintSplitSentencesToTextFile(punctuations, outsentences, 'test1out')\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.3" } }, "nbformat": 4, "nbformat_minor": 2 }