How to identify the subject of a sentence?

Question

Can Python + NLTK be used to identify the subject of a sentence? From what I have learned till now is that a sentence can be broken into a head and its dependents. For e.g.

Answer 1

rake_nltk (pip install rake_nltk) is a python library that wraps nltk and apparently uses the RAKE algorithm.

from rake_nltk import Rake

rake = Rake()

kw = rake.extract_keywords_from_text("Can Python + NLTK be used to identify the subject of a sentence?")

ranked_phrases = rake.get_ranked_phrases()

print(ranked_phrases)

# outputs the keywords ordered by rank
>>> ['used', 'subject', 'sentence', 'python', 'nltk', 'identify']

By default the stopword list from nltk is used. You can provide your custom stopword list and punctuation chars by passing them in the constructor:

rake = Rake(stopwords='mystopwords.txt', punctuations=''',;:!@#$%^*/\''')

By default string.punctuation is used for punctuation.

The constructor also accepts a language keyword which can be any language supported by nltk.

Answer 2

As NLTK book (exercise 29) says, "One common way of defining the subject of a sentence S in English is as the noun phrase that is the child of S and the sibling of VP."

Look at tree example: indeed, "I" is the noun phrase that is the child of S that is the sibling of VP, while "elephant" is not.

Answer 3

You can paper over the issue by doing something like doc = nlp(text.decode('utf8')), but this will likely bring you more bugs in future.

Credits: https://github.com/explosion/spaCy/issues/380

Answer 4

You can use Spacy.

Code

import spacy
nlp = spacy.load('en')
sent = "I shot an elephant"
doc=nlp(sent)

sub_toks = [tok for tok in doc if (tok.dep_ == "nsubj") ]

print(sub_toks) 

Answer 5

Stanford Corenlp Tool can also be used to extract Subject-Relation-Object information of a sentence.

Attaching screenshot of same:

Answer 6

English language has two voices: Active voice and passive voice. Lets take most used voice: Active voice.

It follows subject-verb-object model. To mark the subject, write a rule set with POS tags. Tag the sentence I[NOUN] shot[VERB] an elephant[NOUN]. If you see the first noun is subject, then there is a verb and then there is an object.

If you want to make it more complicated, a sentence- I shot an elephant with a gun. Here the prepositions or subordinate conjunctions like with, at, in can be given roles. Here the sentence will be tagged as I[NOUN] shot[VERB] an elephant[NOUN] with[IN] a gun[NOUN]. You can easily say that word with gets instrumentative role. You can build a rule based system to get role of every word in the sentence.

Also look at the patterns in passive voice and write rules for the same.