Update parsing semantyczny
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parent
452a728a6e
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352
data/parsing_semantyczny.ipynb
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352
data/parsing_semantyczny.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "169e11e8-19c7-47ae-b8af-817e2e474ee7",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Overwriting book.jsgf\n"
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]
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}
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],
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"source": [
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"%%writefile book.jsgf\n",
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"#JSGF V1.0 UTF-8 pl;\n",
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"\n",
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"grammar book;\n",
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"\n",
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"public <rezerwuj> = chcialbym zarezerwowac stolik <dzien_rezerwacji> <godzina_rezerwacji> <liczba_osob> ;\n",
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"\n",
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"<dzien_rezerwacji> = na <dzien> {day};\n",
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"\n",
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"<dzien> = dzisiaj | jutro | poniedzialek | wtorek | srode | czwartek | piatek | sobote | niedziele;\n",
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"\n",
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"<godzina_rezerwacji> = na [godzine] <godzina_z_minutami> {hour};\n",
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"\n",
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"<godzina_z_minutami> = <godzina> [<minuty>];\n",
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"\n",
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"<godzina> = dziewiata | dziesiata | jedenasta | dwunasta;\n",
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"\n",
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"<minuty> = pietnascie | trzydziesci;\n",
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"\n",
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"<liczba_osob> = (na | dla) <liczba> {size} osob;\n",
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"\n",
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"<liczba> = dwie | dwoch | trzy | trzech | cztery | czterech | piec | pieciu;"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "88cc9879-a59c-4c90-adb6-1022c42913e6",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Overwriting order.jsgf\n"
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]
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}
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],
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"source": [
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"%%writefile order.jsgf\n",
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"#JSGF V1.0 UTF-8 pl;\n",
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"\n",
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"grammar order;\n",
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"\n",
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"public <zamow> = (chcialbym | chcialabym) zamowic <danie> <stolik>;\n",
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"\n",
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"<danie> = <potrawa> {dish};\n",
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"\n",
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"<potrawa> = pizza peperoni | spaghetti carbonara | burger szefa;\n",
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"\n",
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"<stolik> = (do stolika | na stolik ) <numer_stolika> {stolik};\n",
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"\n",
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"<numer_stolika> = 100 | 101 | 102 | 103 | 104 | 105;"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "c5ffadfe-ea18-45ab-a9f9-b2cfd3c2fee7",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Overwriting recommend.jsgf\n"
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]
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}
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],
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"source": [
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"%%writefile recommend.jsgf\n",
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"#JSGF V1.0 UTF-8 pl;\n",
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"\n",
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"grammar recommend;\n",
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"\n",
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"public <polec_ogolny> = (jakie|jaki|jaka|jakiego) <jedzenie_napoj> polecasz;\n",
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"\n",
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"<jedzenie_napoj> = <jedzenie_napoj_opcje> {food_or_drink};\n",
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"\n",
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"<jedzenie_napoj_opcje> = jedzenia | picia | napoj | danie | dania;\n",
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"\n",
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"public <polec_danie> = ((jakie|jaki|jaka|jakiego) <danie>) *;\n",
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"\n",
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"public <polec_napoj> = ((jakie|jaki|jaka|jakiego) <napoj>) *;\n",
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"\n",
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"<danie> = <dania> {dish};\n",
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"\n",
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"<dania> = makarony | makaron | pizze | pizza | burgery | burger | salatki | salatka | deser | desery;\n",
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"\n",
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"<napoj> = <napoje> {drink};\n",
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"\n",
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"<napoje> = piwo | piwa | wino | wina | sok | soki | smoothie | kawe | kawy | kawe | herbate | herbata | herbaty;"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "57fb9886-0232-4dd9-b385-7cae1b068f6e",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Grammar(version=1.0, charset=UTF-8, language=pl, name=order)"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import jsgf\n",
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"\n",
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"book_grammar = jsgf.parse_grammar_file('book.jsgf')\n",
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"order_grammar = jsgf.parse_grammar_file('order.jsgf')\n",
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"recommend_grammar = jsgf.parse_grammar_file('recommend.jsgf')\n",
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"order_grammar"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "8f5acde6-4f3c-425d-a202-f361b219922d",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Rule(name='rezerwuj', visible=True, expansion=Sequence(Literal('chcialbym zarezerwowac stolik'), NamedRuleRef('dzien_rezerwacji'), NamedRuleRef('godzina_rezerwacji'), NamedRuleRef('liczba_osob')))]"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"utterance = 'chcialbym zarezerwowac stolik na jutro na godzine dwunasta trzydziesci na piec osob'\n",
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"matched = book_grammar.find_matching_rules(utterance)\n",
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"if not matched:\n",
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" matched = order_grammar.find_matching_rules(utterance)\n",
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"if not matched:\n",
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" matched = recommend_grammar.find_matching_rules(utterance)\n",
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"matched"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "6cb7d2ba-d8ee-403a-bbf3-d7ea3e0475ba",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Rule(name='zamow', visible=True, expansion=Sequence(ParsedAlternativeSet(Literal('chcialbym'), Literal('chcialabym')), Literal('zamowic'), NamedRuleRef('danie'), NamedRuleRef('stolik')))]"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"utterance = 'chcialbym zamowic burger szefa do stolika 104'\n",
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"matched = book_grammar.find_matching_rules(utterance)\n",
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"if not matched:\n",
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" matched = order_grammar.find_matching_rules(utterance)\n",
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"if not matched:\n",
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" matched = recommend_grammar.find_matching_rules(utterance)\n",
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"matched"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "371ee857-418d-4546-8e29-88b6c8706659",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Rule(name='polec_danie', visible=True, expansion=KleeneStar(RequiredGrouping(Sequence(RequiredGrouping(ParsedAlternativeSet(Literal('jakie'), Literal('jaki'), Literal('jaka'), Literal('jakiego'))), NamedRuleRef('danie'))))),\n",
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" Rule(name='polec_napoj', visible=True, expansion=KleeneStar(RequiredGrouping(Sequence(RequiredGrouping(ParsedAlternativeSet(Literal('jakie'), Literal('jaki'), Literal('jaka'), Literal('jakiego'))), NamedRuleRef('napoj')))))]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"utterance = 'jakie makarony polecasz'\n",
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"matched = book_grammar.find_matching_rules(utterance)\n",
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"if not matched:\n",
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" matched = order_grammar.find_matching_rules(utterance)\n",
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"if not matched:\n",
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" matched = recommend_grammar.find_matching_rules(utterance)\n",
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"matched"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "c914cc3d-b297-4e05-917c-6a2f09c0f8a9",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'act': 'recommend', 'slots': [('dish', 'makarony')]}"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def get_dialog_act(rule):\n",
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" slots = []\n",
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" get_slots(rule.expansion, slots)\n",
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" return {'act': rule.grammar.name, 'slots': slots}\n",
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"\n",
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"def get_slots(expansion, slots):\n",
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" if expansion.tag != '':\n",
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" slots.append((expansion.tag, expansion.current_match))\n",
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" return\n",
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"\n",
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" for child in expansion.children:\n",
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" get_slots(child, slots)\n",
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"\n",
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" if not expansion.children and isinstance(expansion, jsgf.NamedRuleRef):\n",
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" get_slots(expansion.referenced_rule.expansion, slots)\n",
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"\n",
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"get_dialog_act(matched[0])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "91eaed10-e8c3-4429-a232-d317b84ec38f",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'act': 'book',\n",
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" 'slots': [('day', 'jutro'), ('hour', 'dziesiata'), ('size', 'trzech')]}"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def nlu(utterance):\n",
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" matched = book_grammar.find_matching_rules(utterance)\n",
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" if not matched:\n",
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" matched = order_grammar.find_matching_rules(utterance)\n",
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" if not matched:\n",
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" matched = recommend_grammar.find_matching_rules(utterance)\n",
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"\n",
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" if matched:\n",
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" return get_dialog_act(matched[0])\n",
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" else:\n",
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" return {'act': 'null', 'slots': []}\n",
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"\n",
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"nlu('chcialbym zarezerwowac stolik na jutro na godzine dziesiata dla trzech osob')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "d85e8543-be59-4c5f-b9f9-27631a899c2a",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'act': 'recommend', 'slots': [('dish', 'makarony')]}"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"nlu('jakie makarony polecasz')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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