I have this text
'''Hi, Mr. Sam D. Richards lives here, 44 West 22nd Street, New York, NY 12345. Can you contact him now? If you need any help, call me on 12345678'''
. How the address part can be extracted from the above text using NLTK? I have tried Stanford NER Tagger
, which gives me only New York
as Location. How to solve this?
noun_phrases() method. With the help of TextBlob. noun_phrases() method, we can get the noun phrases of the sentences by using TextBlob.
re. match(pattern, string): This method checks for a match in a string. It matches if the defined pattern occurs at the beginning of the string. Trying to match 'Artificial' in 'Artificial Intelligence' will match. Let's see an example.
Definitely regular expressions :)
Something like
import re
txt = ...
regexp = "[0-9]{1,3} .+, .+, [A-Z]{2} [0-9]{5}"
address = re.findall(regexp, txt)
# address = ['44 West 22nd Street, New York, NY 12345']
Explanation:
[0-9]{1,3}
: 1 to 3 digits, the address number
(space)
: a space between the number and the street name
.+
: street name, any character for any number of occurrences
,
: a comma and a space before the city
.+
: city, any character for any number of occurrences
,
: a comma and a space before the state
[A-Z]{2}
: exactly 2 uppercase chars from A to Z
[0-9]{5}
: 5 digits
re.findall(expr, string)
will return an array with all the occurrences found.
Pyap works best not just for this particular example but also for other addresses contained in texts.
text = ...
addresses = pyap.parse(text, country='US')
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