add nlg
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Adrian
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"<div class=\"alert alert-block alert-info\">\n",
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"<h1> Systemy Dialogowe </h1>\n",
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"<h2> 7. <i>Parsing semantyczny z wykorzystaniem gramatyk</i> [laboratoria]</h2> \n",
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"<h3> Marek Kubis (2021)</h3>\n",
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"</div>\n",
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"\n",
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""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Parsing semantyczny z wykorzystaniem gramatyk\n",
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"=============================================\n",
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"\n",
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"Wartości slotów możemy wydobywać z wypowiedzi użytkownika korzystając z takich technik, jak:\n",
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"\n",
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" - wyszukiwanie słów kluczowych w tekście,\n",
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"\n",
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" - dopasowywanie wzorców zbudowanych przy użyciu wyrażeń regularnych,\n",
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"\n",
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" - parsery regułowe (temat dzisiejszych zajęć),\n",
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"\n",
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" - uczenie maszynowe (temat kolejnych zajęć)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Przykłady parserów regułowych\n",
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"-----------------------------\n",
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"\n",
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" - [Phoenix](http://wiki.speech.cs.cmu.edu/olympus/index.php/Phoenix_Server) — parser gramatyk\n",
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" bezkontekstowych whodzący w skład systemu dialogowego [Olympus](http://wiki.speech.cs.cmu.edu/olympus/index.php/Olympus)\n",
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"\n",
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" - Parsery [DCG](https://www.swi-prolog.org/pldoc/man?section=DCG) (Definite Clause Grammars) języka [Prolog](https://www.swi-prolog.org/)\n",
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"\n",
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" - [JSpeech Grammar Format](https://www.w3.org/TR/jsgf/) (JSGF)\n",
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"\n",
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"Przykład\n",
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"--------\n",
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"Zapiszmy w JSGF gramatykę semantyczną dla aktu dialogowego reprezentującego zamiar rezerwacji\n",
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"stolika w restauracji."
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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": 51,
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"metadata": {},
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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> = chciałbym zarezerwować <ilosc_biletow> <tytul_filmu> [<dzien_rezerwacji>] [<godzina_rezerwacji>];\n",
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"\n",
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"<ilosc_biletow> = <liczba> {ilosc} (bilety | biletów);\n",
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"\n",
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"<liczba> = dwa | trzy | cztery |1|2|3|4|5|6;\n",
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"\n",
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"<tytul_filmu> = na [film] <tytul> {tytul};\n",
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"\n",
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"<tytul> = Batman | Uncharted | Pitbull;\n",
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"\n",
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"<dzien_rezerwacji> = na <dzien> {dzien};\n",
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"\n",
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"<dzien> = dzisiaj | jutro | poniedziałek | wtorek | środę | czwartek | piątek | sobotę | niedzielę;\n",
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"\n",
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"<godzina_rezerwacji> = na [godzinę] <godzina_z_minutami> {godzina};\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> = dziewiątą | dziesiątą | jedenastą | dwunastą;\n",
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"\n",
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"<minuty> = pietnaście | trzydzieści;\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Parser akceptujący powyższą gramatykę utworzymy korzystając z biblioteki [pyjsgf](https://github.com/Danesprite/pyjsgf)."
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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": 52,
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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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"Grammar(version=1.0, charset=UTF-8, language=pl, name=book)"
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]
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},
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"execution_count": 52,
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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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"book_grammar"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Wykorzystajmy gramatykę `book.jsgf` do analizy następującej wypowiedzi"
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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": 53,
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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='rezerwuj', visible=True, expansion=Sequence(Literal('chciałbym zarezerwować'), NamedRuleRef('ilosc_biletow'), NamedRuleRef('tytul_filmu'), OptionalGrouping(NamedRuleRef('dzien_rezerwacji')), OptionalGrouping(NamedRuleRef('godzina_rezerwacji'))))]"
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]
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},
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"execution_count": 53,
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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 = 'chciałbym zarezerwować 1 biletów na film Pitbull'\n",
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"matched = book_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": "markdown",
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"metadata": {},
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"source": [
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"Reprezentację znaczenia można wydobyć ze sparsowanej wypowiedzi na wiele sposobów. My do\n",
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"wydobywania slotów wykorzystamy mechanizm tagów JSGF a za nazwę aktu dialogowego przyjmiemy nazwę\n",
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"gramatyki. Wzorując się na [DSTC2](https://github.com/matthen/dstc) wynikową ramę zapiszemy korzystając ze słownika o polach `act` i `slots`."
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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": 54,
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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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"{'act': 'book',\n",
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" 'slots': [('ilosc', '1'),\n",
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" ('tytul', 'Pitbull'),\n",
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" ('dzien', None),\n",
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" ('godzina', None)]}"
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]
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},
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"execution_count": 54,
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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": "markdown",
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"metadata": {},
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"source": [
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"Łącząc powyższe funkcje możemy zbudować prosty moduł NLU."
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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": 41,
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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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"{'act': 'null', 'slots': []}"
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]
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},
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"execution_count": 41,
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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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"\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('chciałbym zarezerwować dwa bilety na film Pitbull')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Problemy\n",
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"--------\n",
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"\n",
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" - Co z normalizacją wyrażeń liczbowych takich, jak godziny, daty czy numery telefonów?\n",
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"\n",
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" - Co w przypadku gdy więcej niż jedna reguła zostanie dopasowana?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Zadanie\n",
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"-------\n",
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"Zaimplementować analizator języka naturalnego (NLU) na potrzeby realizowanego agenta dialogowego.\n",
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"\n",
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"Moduł powinien być zbudowany z wykorzystaniem parsingu regułowego i/lub technik uczenia maszynowego.\n",
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"\n",
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"Przygotować skrypt `evaluate.py` wyznaczający *dokładność* (ang. accuracy) analizatora względem zgromadzonego korpusu eksperymentalnego,\n",
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"tj. stosunek liczby wypowiedzi użytkownika, w których akty dialogowe zostały rozpoznane prawidłowo do liczby wszystkich wypowiedzi użytkownika w korpusie.\n",
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"\n",
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"Analizator języka naturalnego umieścić w gałęzi `master` repozytorium projektowego. Skrypt `evaluate.py` umieścić w katalogu głównym tej gałęzi.\n",
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"\n",
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"Termin: 4.05.2022, godz. 23:59."
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]
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}
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],
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"metadata": {
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"author": "Marek Kubis",
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"email": "mkubis@amu.edu.pl",
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"jupytext": {
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"cell_metadata_filter": "-all",
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"main_language": "python",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"lang": "pl",
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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": "3.7.3"
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},
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"subtitle": "7.Parsing semantyczny z wykorzystaniem gramatyk[laboratoria]",
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"title": "Systemy Dialogowe",
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"year": "2021"
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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@ -0,0 +1,74 @@
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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": 6,
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"id": "978f5cd3-eb2e-45c4-ace8-f105ccd4cb74",
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"metadata": {},
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'jsgf'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_12388/3924194050.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mmodules\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDST\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mDst\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mmodules\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAJN\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mAjn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\Adi\\Szkoła\\Semestr 8\\Systemy dialogowe\\Projekt\\SystemyDialogowe\\modules\\AJN.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mjsgf\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mos\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mlistdir\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0misfile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mjoin\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mmypath\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"./grammar/\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'jsgf'"
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]
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}
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],
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"source": [
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"from modules.DST import Dst\n",
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"from modules.AJN import Ajn\n",
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"\n",
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"\n",
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"\n",
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"if __name__ == \"__main__\":\n",
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" nlg = nlg.Nlg()\n",
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" nlu = nlu.Nlu()\n",
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" dst = dst.Dst()\n",
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"\n",
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" next_question = dst.get_next_question()\n",
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" while (next_question):\n",
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" print(next_question)\n",
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" response = input()\n",
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" res_tokenized = nlu.tokenize(response)\n",
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" dst.save_answer(res_tokenized['slots'])\n",
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" next_question = dst.get_next_question()\n",
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"\n",
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" print(dst.checklist)"
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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": null,
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"id": "bec70f0e-c4e9-488e-8748-6d976a67beae",
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.9.7"
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}
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},
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"nbformat": 4,
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||||
"nbformat_minor": 5
|
||||
}
|
||||
|
|
@ -0,0 +1,326 @@
|
|||
from nltk.chat.util import Chat, reflections
|
||||
|
||||
pairs = (
|
||||
(
|
||||
r"I need (.*)",
|
||||
(
|
||||
"Why do you need %1?",
|
||||
"Would it really help you to get %1?",
|
||||
"Are you sure you need %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"who created you (.*)",
|
||||
(
|
||||
"ELIZA was invented in 1966 by Weizenbaum. Why %1?",
|
||||
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Why don\'t you (.*)",
|
||||
(
|
||||
"Do you really think I don't %1?",
|
||||
"Perhaps eventually I will %1.",
|
||||
"Do you really want me to %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Why can\'t I (.*)",
|
||||
(
|
||||
"Do you think you should be able to %1?",
|
||||
"If you could %1, what would you do?",
|
||||
"I don't know -- why can't you %1?",
|
||||
"Have you really tried?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"I can\'t (.*)",
|
||||
(
|
||||
"How do you know you can't %1?",
|
||||
"Perhaps you could %1 if you tried.",
|
||||
"What would it take for you to %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"I am (.*)",
|
||||
(
|
||||
"Did you come to me because you are %1?",
|
||||
"How long have you been %1?",
|
||||
"How do you feel about being %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"I\'m (.*)",
|
||||
(
|
||||
"How does being %1 make you feel?",
|
||||
"Do you enjoy being %1?",
|
||||
"Why do you tell me you're %1?",
|
||||
"Why do you think you're %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Are you (.*)",
|
||||
(
|
||||
"Why does it matter whether I am %1?",
|
||||
"Would you prefer it if I were not %1?",
|
||||
"Perhaps you believe I am %1.",
|
||||
"I may be %1 -- what do you think?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"What (.*)",
|
||||
(
|
||||
"Why do you ask?",
|
||||
"How would an answer to that help you?",
|
||||
"What do you think?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"How (.*)",
|
||||
(
|
||||
"How do you suppose?",
|
||||
"Perhaps you can answer your own question.",
|
||||
"What is it you're really asking?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Because (.*)",
|
||||
(
|
||||
"Is that the real reason?",
|
||||
"What other reasons come to mind?",
|
||||
"Does that reason apply to anything else?",
|
||||
"If %1, what else must be true?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"(.*) sorry (.*)",
|
||||
(
|
||||
"There are many times when no apology is needed.",
|
||||
"What feelings do you have when you apologize?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Hello(.*)",
|
||||
(
|
||||
"Hello... I'm glad you could drop by today.",
|
||||
"Hi there... how are you today?",
|
||||
"Hello, how are you feeling today?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"I think (.*)",
|
||||
("Do you doubt %1?", "Do you really think so?", "But you're not sure %1?"),
|
||||
),
|
||||
(
|
||||
r"(.*) friend (.*)",
|
||||
(
|
||||
"Tell me more about your friends.",
|
||||
"When you think of a friend, what comes to mind?",
|
||||
"Why don't you tell me about a childhood friend?",
|
||||
),
|
||||
),
|
||||
(r"Yes", ("You seem quite sure.", "OK, but can you elaborate a bit?")),
|
||||
(
|
||||
r"(.*) computer(.*)",
|
||||
(
|
||||
"Are you really talking about me?",
|
||||
"Does it seem strange to talk to a computer?",
|
||||
"How do computers make you feel?",
|
||||
"Do you feel threatened by computers?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Is it (.*)",
|
||||
(
|
||||
"Do you think it is %1?",
|
||||
"Perhaps it's %1 -- what do you think?",
|
||||
"If it were %1, what would you do?",
|
||||
"It could well be that %1.",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"It is (.*)",
|
||||
(
|
||||
"You seem very certain.",
|
||||
"If I told you that it probably isn't %1, what would you feel?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Can you (.*)",
|
||||
(
|
||||
"What makes you think I can't %1?",
|
||||
"If I could %1, then what?",
|
||||
"Why do you ask if I can %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Czy mogę (.*)",
|
||||
(
|
||||
"Być może nie chcesz %1.",
|
||||
"Czy chcesz mieć możliwość %1?",
|
||||
"Gdybyś mógł %1, czy byś?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Ty jesteś (.*)",
|
||||
(
|
||||
"Jak myślisz, dlaczego jestem %1?",
|
||||
"Czy cieszy cię myśl, że jestem %1?",
|
||||
"Być może chciałbyś, żebym był %1.",
|
||||
"Może naprawdę mówisz o sobie?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Jesteś (.*)",
|
||||
(
|
||||
"Dlaczego mówisz, że jestem %1?",
|
||||
"Jak myślisz, dlaczego jestem %1?",
|
||||
"Mówimy o tobie, czy o mnie?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Ja nie (.*)",
|
||||
("Czy naprawdę nie %1?", "Dlaczego nie %1?", "Czy chcesz %1?"),
|
||||
),
|
||||
(
|
||||
r"Ja czuję (.*)",
|
||||
(
|
||||
"Dobrze, powiedz mi więcej o tych uczuciach.",
|
||||
"Czy często czujesz %1?",
|
||||
"Kiedy zwykle czujesz %1?",
|
||||
"Kiedy czujesz % 1, co robisz?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Mam (.*)",
|
||||
(
|
||||
"Dlaczego mówisz mi, że masz %1?",
|
||||
"Czy naprawdę masz %1?",
|
||||
"Teraz, kiedy masz %1, co zrobisz dalej?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Ja chcę (.*)",
|
||||
(
|
||||
"Czy możesz wyjaśnić, dlaczego chcesz %1?",
|
||||
"Dlaczego %1?",
|
||||
"Kto jeszcze wie, że chcesz %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Jest (.*)",
|
||||
(
|
||||
"Myślisz, że jest %1?",
|
||||
"Prawdopodobnie istnieje %1.",
|
||||
"Czy chciałbyś, aby był %1?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Mój (.*)",
|
||||
(
|
||||
"Rozumiem, twój %1.",
|
||||
"Dlaczego mówisz, że twój %1?",
|
||||
"Kiedy Twój %1, jak się czujesz?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"Ty (.*)",
|
||||
(
|
||||
"Powinniśmy rozmawiać o Tobie, nie o mnie.",
|
||||
"Dlaczego tak o mnie mówisz?",
|
||||
"Dlaczego obchodzi cię, czy ja %1?",
|
||||
),
|
||||
),
|
||||
(r"Dlaczego (.*)", ("Powiedz mi dlaczego %1?", "Wydaje ci się że, %1?")),
|
||||
(
|
||||
r"Ja chcę (.*)",
|
||||
(
|
||||
"Co by dla ciebie znaczyło, gdybyś dostał %1?",
|
||||
"Dlaczego chcesz %1?",
|
||||
"Co byś zrobił, gdybyś dostał %1?",
|
||||
"Jeśli masz %1, co byś zrobił?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"(.*) mother(.*)",
|
||||
(
|
||||
"Tell me more about your mother.",
|
||||
"What was your relationship with your mother like?",
|
||||
"How do you feel about your mother?",
|
||||
"How does this relate to your feelings today?",
|
||||
"Good family relations are important.",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"(.*) father(.*)",
|
||||
(
|
||||
"Tell me more about your father.",
|
||||
"How did your father make you feel?",
|
||||
"How do you feel about your father?",
|
||||
"Does your relationship with your father relate to your feelings today?",
|
||||
"Do you have trouble showing affection with your family?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"(.*) child(.*)",
|
||||
(
|
||||
"Did you have close friends as a child?",
|
||||
"What is your favorite childhood memory?",
|
||||
"Do you remember any dreams or nightmares from childhood?",
|
||||
"Did the other children sometimes tease you?",
|
||||
"How do you think your childhood experiences relate to your feelings today?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"(.*)\?",
|
||||
(
|
||||
"Why do you ask that?",
|
||||
"Please consider whether you can answer your own question.",
|
||||
"Perhaps the answer lies within yourself?",
|
||||
"Why don't you tell me?",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"quit",
|
||||
(
|
||||
"Thank you for talking with me.",
|
||||
"Good-bye.",
|
||||
"Thank you, that will be $150. Have a good day!",
|
||||
),
|
||||
),
|
||||
(
|
||||
r"(.*)",
|
||||
(
|
||||
"Please tell me more.",
|
||||
"Let's change focus a bit... Tell me about your family.",
|
||||
"Can you elaborate on that?",
|
||||
"Why do you say that %1?",
|
||||
"I see.",
|
||||
"Very interesting.",
|
||||
"%1.",
|
||||
"I see. And what does that tell you?",
|
||||
"How does that make you feel?",
|
||||
"How do you feel when you say that?",
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
eliza_chatbot = Chat(pairs, reflections)
|
||||
|
||||
|
||||
def eliza_chat():
|
||||
print("Psychiatrist\n---------")
|
||||
print("Talk to the program by typing in plain English, using normal upper-")
|
||||
print('and lower-case letters and punctuation. Enter "quit" when done.')
|
||||
print("=" * 72)
|
||||
print("Hello. My name is Eliza.\nHow are you feeling today?")
|
||||
|
||||
eliza_chatbot.converse()
|
||||
|
||||
|
||||
def demo():
|
||||
eliza_chat()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
demo()
|
||||
|
|
@ -277,7 +277,7 @@
|
|||
"notebook_metadata_filter": "-all"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
|
|
@ -292,7 +292,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.3"
|
||||
"version": "3.7.13"
|
||||
},
|
||||
"subtitle": "7.Parsing semantyczny z wykorzystaniem gramatyk[laboratoria]",
|
||||
"title": "Systemy Dialogowe",
|
||||
|
|
|
|||
|
|
@ -0,0 +1,163 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "encouraging-december",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdin",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
">>> chce 2 bilety\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"tytul\n",
|
||||
"{'ilosc': '2', 'tytul': None, 'dzien': None, 'godzina': None}\n",
|
||||
"Na jaki film ma zostać dokonana rezerwacja?\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdin",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
">>> chce na film batman\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"ilosc\n",
|
||||
"{'ilosc': None, 'tytul': 'Batman', 'dzien': None, 'godzina': None}\n",
|
||||
"Ile biletów ma zostać zarezerwowanych?\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdin",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
">>> chce 2 bilety\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"tytul\n",
|
||||
"{'ilosc': '2', 'tytul': None, 'dzien': None, 'godzina': None}\n",
|
||||
"Na jaki film ma zostać dokonana rezerwacja?\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdin",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
">>> chce 2 bilety na film batman\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"dzien\n",
|
||||
"{'ilosc': '2', 'tytul': 'Batman', 'dzien': None, 'godzina': None}\n",
|
||||
"Na który dzień ma być dokonana rezerwacja?\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdin",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
">>> chce na jutro\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"ilosc\n",
|
||||
"{'ilosc': None, 'tytul': None, 'dzien': 'jutro', 'godzina': None}\n",
|
||||
"Ile biletów ma zostać zarezerwowanych?\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"ename": "KeyboardInterrupt",
|
||||
"evalue": "Interrupted by user",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-2-0b584a7b5a30>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0mtext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'>>>'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 15\u001b[0m \u001b[0mframe\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0majn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36mraw_input\u001b[0;34m(self, prompt)\u001b[0m\n\u001b[1;32m 849\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_ident\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 850\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_header\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 851\u001b[0;31m \u001b[0mpassword\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 852\u001b[0m )\n\u001b[1;32m 853\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36m_input_request\u001b[0;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[1;32m 890\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 891\u001b[0m \u001b[0;31m# re-raise KeyboardInterrupt, to truncate traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 892\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Interrupted by user\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 893\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 894\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Invalid Message:\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mKeyboardInterrupt\u001b[0m: Interrupted by user"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from DST import Dst\n",
|
||||
"from AJN import *\n",
|
||||
"from NLG import nlg\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"if __name__ == \"__main__\":\n",
|
||||
" \n",
|
||||
" dst = Dst()\n",
|
||||
" next_question = dst.get_next_question()\n",
|
||||
" while (next_question):\n",
|
||||
" \n",
|
||||
" \n",
|
||||
" text = input('>>>')\n",
|
||||
" frame = ajn(text)\n",
|
||||
" \n",
|
||||
" dst.save_answer(frame['slots'])\n",
|
||||
" \n",
|
||||
" next_question = dst.get_next_question()\n",
|
||||
" print(next_question)\n",
|
||||
" print(dst.checklist)\n",
|
||||
"# print(frame['act'])\n",
|
||||
" nlg(next_question)\n",
|
||||
"\n",
|
||||
" \n",
|
||||
" \n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "yellow-acquisition",
|
||||
"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": "3.7.3"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
|
|
@ -0,0 +1,50 @@
|
|||
import jsgf
|
||||
from os import listdir
|
||||
from os.path import isfile, join
|
||||
|
||||
mypath = "./grammar/"
|
||||
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
|
||||
|
||||
grammars = []
|
||||
|
||||
for grammarFile in onlyfiles:
|
||||
grammar = jsgf.parse_grammar_file(mypath + grammarFile)
|
||||
grammars.append(grammar)
|
||||
|
||||
class Ajn:
|
||||
|
||||
|
||||
|
||||
def __init__(self, grammars = None):
|
||||
self.grammars = grammars
|
||||
|
||||
def get_dialog_act(rule):
|
||||
slots = []
|
||||
get_slots(rule.expansion, slots)
|
||||
return {'act': rule.grammar.name, 'slots': slots}
|
||||
|
||||
def get_slots(expansion, slots):
|
||||
if expansion.tag != '':
|
||||
slots.append((expansion.tag, expansion.current_match))
|
||||
return
|
||||
|
||||
for child in expansion.children:
|
||||
get_slots(child, slots)
|
||||
|
||||
if not expansion.children and isinstance(expansion, jsgf.NamedRuleRef):
|
||||
get_slots(expansion.referenced_rule.expansion, slots)
|
||||
|
||||
def nlu(utterance):
|
||||
matched = None
|
||||
for grammar in grammars:
|
||||
matched = grammar.find_matching_rules(utterance)
|
||||
if matched:
|
||||
break
|
||||
|
||||
if matched:
|
||||
return get_dialog_act(matched[0])
|
||||
else:
|
||||
return {'act': 'null', 'slots': []}
|
||||
|
||||
|
||||
ajn = Ajn()
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
class Dst:
|
||||
def __init__(self):
|
||||
self.messages = []
|
||||
self.checklist = {
|
||||
"ilosc": None,
|
||||
"tytul": None,
|
||||
"dzien": None,
|
||||
"godzina": None
|
||||
}
|
||||
self.history = []
|
||||
|
||||
def store(self, message):
|
||||
self.messages.append(message)
|
||||
|
||||
def get_messages(self):
|
||||
return self.messages
|
||||
|
||||
def get_next_question(self):
|
||||
for key, value in self.checklist.items():
|
||||
if value == None:
|
||||
return key
|
||||
|
||||
def save_answer(self, slots):
|
||||
for slot in slots:
|
||||
self.checklist[slot[0]] = slot[1]
|
||||
|
||||
self.messages.append(slots)
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
def nlg(query):
|
||||
if query == 'dzien':
|
||||
print("Na który dzień ma być dokonana rezerwacja?")
|
||||
if query == 'godzina':
|
||||
print("Na którą godzinę ma być dokonana rezerwacja?")
|
||||
if query == 'ilosc':
|
||||
print("Ile biletów ma zostać zarezerwowanych?")
|
||||
if query == 'tytul':
|
||||
print("Na jaki film ma zostać dokonana rezerwacja?")
|
||||
|
||||
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Loading…
Reference in New Issue