I used NLTK's ne_chunk
to extract named entities from a text:
my_sent = "WASHINGTON -- In the wake of a string of abuses by New York police officers in the 1990s, Loretta E. Lynch, the top federal prosecutor in Brooklyn, spoke forcefully about the pain of a broken trust that African-Americans felt and said the responsibility for repairing generations of miscommunication and mistrust fell to law enforcement."
nltk.ne_chunk(my_sent, binary=True)
But I can't figure out how to save these entities to a list? E.g. –
print Entity_list
('WASHINGTON', 'New York', 'Loretta', 'Brooklyn', 'African')
Thanks.
nltk.ne_chunk
returns a nested nltk.tree.Tree
object so you would have to traverse the Tree
object to get to the NEs.
Take a look at Named Entity Recognition with Regular Expression: NLTK
>>> from nltk import ne_chunk, pos_tag, word_tokenize
>>> from nltk.tree import Tree
>>>
>>> def get_continuous_chunks(text):
... chunked = ne_chunk(pos_tag(word_tokenize(text)))
... continuous_chunk = []
... current_chunk = []
... for i in chunked:
... if type(i) == Tree:
... current_chunk.append(" ".join([token for token, pos in i.leaves()]))
... if current_chunk:
... named_entity = " ".join(current_chunk)
... if named_entity not in continuous_chunk:
... continuous_chunk.append(named_entity)
... current_chunk = []
... else:
... continue
... return continuous_chunk
...
>>> my_sent = "WASHINGTON -- In the wake of a string of abuses by New York police officers in the 1990s, Loretta E. Lynch, the top federal prosecutor in Brooklyn, spoke forcefully about the pain of a broken trust that African-Americans felt and said the responsibility for repairing generations of miscommunication and mistrust fell to law enforcement."
>>> get_continuous_chunks(my_sent)
['WASHINGTON', 'New York', 'Loretta E. Lynch', 'Brooklyn']
>>> my_sent = "How's the weather in New York and Brooklyn"
>>> get_continuous_chunks(my_sent)
['New York', 'Brooklyn']