def parse_all(user_input: str, culture: str) -> List[ModelResult]: return [ # Number recognizer - This function will find any number from the input # E.g "I have two apples" will return "2". Recognizers.recognize_number(user_input, culture), # Ordinal number recognizer - This function will find any ordinal number # E.g "eleventh" will return "11". Recognizers.recognize_ordinal(user_input, culture), # Percentage recognizer - This function will find any number presented as percentage # E.g "one hundred percents" will return "100%" Recognizers.recognize_percentage(user_input, culture), # Age recognizer - This function will find any age number presented # E.g "After ninety five years of age, perspectives change" will return "95 Year" Recognizers.recognize_age(user_input, culture), # Currency recognizer - This function will find any currency presented # E.g "Interest expense in the 1988 third quarter was $ 75.3 million" will return "75300000 Dollar" Recognizers.recognize_currency(user_input, culture), # Dimension recognizer - This function will find any dimension presented # E.g "The six-mile trip to my airport hotel that had taken 20 minutes earlier in the day took more than three hours." will return "6 Mile" Recognizers.recognize_dimension(user_input, culture), # Temperature recognizer - This function will find any temperature presented # E.g "Set the temperature to 30 degrees celsius" will return "30 C" Recognizers.recognize_temperature(user_input, culture), # DateTime recognizer - This function will find any Date even if its write in colloquial language - # E.g "I'll go back 8pm today" will return "2017-10-04 20:00:00" Recognizers.recognize_datetime(user_input, culture) ]
def retrieve_punctuality(raw_value): p_result = Recognizers.recognize_percentage(raw_value, Culture.Chinese) if len(p_result) == 0: f_result = Recognizers.recognize_number(raw_value, Culture.Chinese) if len(f_result) == 0: return 0.0 return float(f_result[0].resolution['value']) return float(p_result[0].resolution['value'].rstrip('%')) / 100
def _parse_all_entities(user_input: str, culture: str) -> List[Dict[Text, Any]]: """ This is the main method that does the entity extraction work. For more details: https://github.com/Microsoft/Recognizers-Text/tree/master/Python#api-documentation """ return [ # Number recognizer - This function will find any number from the input # E.g "I have two apples" will return "2". Recognizers.recognize_number(user_input, culture), # Ordinal number recognizer - This function will find any ordinal number # E.g "eleventh" will return "11". Recognizers.recognize_ordinal(user_input, culture), # Percentage recognizer - This function will find any number presented as percentage # E.g "one hundred percents" will return "100%" Recognizers.recognize_percentage(user_input, culture), # Age recognizer - This function will find any age number presented # E.g "After ninety five years of age, perspectives change" will return # "95 Year" Recognizers.recognize_age(user_input, culture), # Currency recognizer - This function will find any currency presented # E.g "Interest expense in the 1988 third quarter was $ 75.3 million" # will return "75300000 Dollar" Recognizers.recognize_currency(user_input, culture), # Temperature recognizer - This function will find any temperature presented # E.g "Set the temperature to 30 degrees celsius" will return "30 C" Recognizers.recognize_temperature(user_input, culture), # DateTime recognizer - This function will find any Date even if its write in colloquial language - # E.g "I'll go back 8pm today" will return "2017-10-04 20:00:00" Recognizers.recognize_datetime(user_input, culture), # PhoneNumber recognizer will find any phone number presented # E.g "My phone number is ( 19 ) 38294427." Recognizers.recognize_phone_number(user_input, culture), # Email recognizer will find any phone number presented # E.g "Please write to me at [email protected] for more information on task # #A1" Recognizers.recognize_email(user_input, culture), ]
def parse_all(user_input: str, culture: str): return [ recognizers_suite.recognize_number(user_input, culture), recognizers_suite.recognize_dimension(user_input, culture), ]