diff --git a/nltk/parse/__init__.py b/nltk/parse/__init__.py
index dba46c595c..66441de612 100644
--- a/nltk/parse/__init__.py
+++ b/nltk/parse/__init__.py
@@ -78,3 +78,4 @@
 from nltk.parse.evaluate import DependencyEvaluator
 from nltk.parse.transitionparser import TransitionParser
 from nltk.parse.bllip import BllipParser
+from nltk.parse.corenlp import CoreNLPParser, CoreNLPDependencyParser
diff --git a/nltk/parse/corenlp.py b/nltk/parse/corenlp.py
new file mode 100644
index 0000000000..38e406cd20
--- /dev/null
+++ b/nltk/parse/corenlp.py
@@ -0,0 +1,672 @@
+# -*- coding: utf-8 -*-
+# Natural Language Toolkit: Interface to the CoreNLP REST API.
+#
+# Copyright (C) 2001-2016 NLTK Project
+# Author: Dmitrijs Milajevs <dimazest@gmail.com>
+#
+# URL: <http://nltk.org/>
+# For license information, see LICENSE.TXT
+
+from __future__ import unicode_literals
+
+import re
+import json
+import time
+import socket
+
+import requests
+
+from nltk.internals import find_jar_iter, config_java, java, _java_options
+
+from nltk.parse.api import ParserI
+from nltk.tokenize.api import TokenizerI
+from nltk.parse.dependencygraph import DependencyGraph
+from nltk.tree import Tree
+
+_stanford_url = 'http://stanfordnlp.github.io/CoreNLP/'
+
+
+class CoreNLPServerError(EnvironmentError):
+    """Exceptions associated with the Core NLP server."""
+
+
+def try_port(port=0):
+    sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+    sock.bind(('', port))
+
+    p = sock.getsockname()[1]
+    sock.close()
+
+    return p
+
+
+class CoreNLPServer(object):
+
+    _MODEL_JAR_PATTERN = r'stanford-corenlp-(\d+)\.(\d+)\.(\d+)-models\.jar'
+    _JAR = r'stanford-corenlp-(\d+)\.(\d+)\.(\d+)\.jar'
+
+    def __init__(
+        self, path_to_jar=None, path_to_models_jar=None, verbose=False,
+        java_options=None, corenlp_options=None, port=None,
+    ):
+
+        if corenlp_options is None:
+            corenlp_options = [
+                '-preload', 'tokenize,ssplit,pos,lemma,parse,depparse',
+            ]
+
+        jars = list(find_jar_iter(
+            self._JAR,
+            path_to_jar,
+            env_vars=('CORENLP', ),
+            searchpath=(),
+            url=_stanford_url,
+            verbose=verbose,
+            is_regex=True,
+        ))
+
+        # find the most recent code and model jar
+        stanford_jar = max(
+            jars,
+            key=lambda model_name: re.match(self._JAR, model_name)
+        )
+
+        if port is None:
+            try:
+                port = try_port(9000)
+            except socket.error:
+                port = try_port()
+                corenlp_options.append(str(port))
+        else:
+            try_port(port)
+
+        self.url = 'http://localhost:{}'.format(port)
+
+        model_jar = max(
+            find_jar_iter(
+                self._MODEL_JAR_PATTERN,
+                path_to_models_jar,
+                env_vars=('CORENLP_MODELS', ),
+                searchpath=(),
+                url=_stanford_url,
+                verbose=verbose,
+                is_regex=True,
+            ),
+            key=lambda model_name: re.match(self._MODEL_JAR_PATTERN, model_name)
+        )
+
+        self.verbose = verbose
+
+        self._classpath = stanford_jar, model_jar
+
+        self.corenlp_options = corenlp_options
+        self.java_options = java_options or ['-mx2g']
+
+    def start(self):
+        cmd = ['edu.stanford.nlp.pipeline.StanfordCoreNLPServer']
+
+        if self.corenlp_options:
+            cmd.extend(self.corenlp_options)
+
+        # Configure java.
+        default_options = ' '.join(_java_options)
+        config_java(options=self.java_options, verbose=self.verbose)
+
+        try:
+            # TODO: it's probably a bad idea to pipe stdout, as it will
+            #       accumulate when lots of text is being parsed.
+            self.popen = java(
+                cmd,
+                classpath=self._classpath,
+                blocking=False,
+                stdout='pipe',
+                stderr='pipe',
+            )
+        finally:
+            # Return java configurations to their default values.
+            config_java(options=default_options, verbose=self.verbose)
+
+        # Check that the server is istill running.
+        returncode = self.popen.poll()
+        if returncode is not None:
+            _, stderrdata = self.popen.communicate()
+            raise CoreNLPServerError(
+                returncode,
+                'Could not start the server. '
+                'The error was: {}'.format(stderrdata.decode('ascii'))
+            )
+
+        for i in range(30):
+            try:
+                response = requests.get(requests.compat.urljoin(self.url, 'live'))
+            except requests.exceptions.ConnectionError:
+                time.sleep(1)
+            else:
+                if response.ok:
+                    break
+        else:
+            raise CoreNLPServerError(
+                'Could not connect to the server.'
+            )
+
+        for i in range(60):
+            try:
+                response = requests.get(requests.compat.urljoin(self.url, 'ready'))
+            except requests.exceptions.ConnectionError:
+                time.sleep(1)
+            else:
+                if response.ok:
+                    break
+        else:
+            raise CoreNLPServerError(
+                'The server is not ready.'
+            )
+
+    def stop(self):
+        self.popen.terminate()
+        self.popen.wait()
+
+    def __enter__(self):
+        self.start()
+
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self.stop()
+        return False
+
+
+class GenericCoreNLPParser(ParserI, TokenizerI):
+    """Interface to the CoreNLP Parser."""
+
+    def __init__(self, url='http://localhost:9000', encoding='utf8'):
+
+        self.url = url
+        self.encoding = encoding
+
+        self.session = requests.Session()
+
+    def parse_sents(self, sentences, *args, **kwargs):
+        """Parse multiple sentences.
+
+        Takes multiple sentences as a list where each sentence is a list of
+        words. Each sentence will be automatically tagged with this
+        CoreNLPParser instance's tagger.
+
+        If a whitespace exists inside a token, then the token will be treated as
+        several tokens.
+
+        :param sentences: Input sentences to parse
+        :type sentences: list(list(str))
+        :rtype: iter(iter(Tree))
+        """
+
+        sentences = (' '.join(words) for words in sentences)
+        return self.raw_parse_sents(sentences, *args, **kwargs)
+
+    def raw_parse(self, sentence, properties=None, *args, **kwargs):
+        """Parse a sentence.
+
+        Takes a sentence as a string; before parsing, it will be automatically
+        tokenized and tagged by the CoreNLP Parser.
+
+        :param sentence: Input sentence to parse
+        :type sentence: str
+        :rtype: iter(Tree)
+        """
+        default_properties = {
+            'tokenize.whitespace': 'false',
+        }
+        default_properties.update(properties or {})
+
+        return next(
+            self.raw_parse_sents(
+                [sentence],
+                properties=default_properties,
+                *args,
+                **kwargs
+            )
+        )
+
+    def api_call(self, data, properties=None):
+        default_properties = {
+            'outputFormat': 'json',
+            'annotators': 'tokenize,pos,lemma,ssplit,{parser_annotator}'.format(
+                parser_annotator=self.parser_annotator,
+            ),
+        }
+
+        default_properties.update(properties or {})
+
+        response = self.session.post(
+            self.url,
+            params={
+                'properties': json.dumps(default_properties),
+            },
+            data=data.encode(self.encoding),
+            timeout=60,
+        )
+
+        response.raise_for_status()
+
+        return response.json()
+
+    def raw_parse_sents(
+        self,
+        sentences,
+        verbose=False,
+        properties=None,
+        *args,
+        **kwargs
+    ):
+        """Parse multiple sentences.
+
+        Takes multiple sentences as a list of strings. Each sentence will be
+        automatically tokenized and tagged.
+
+        :param sentences: Input sentences to parse.
+        :type sentences: list(str)
+        :rtype: iter(iter(Tree))
+
+        """
+        default_properties = {
+            'ssplit.isOneSentence': 'true',
+        }
+
+        default_properties.update(properties or {})
+
+        for sentence in sentences:
+            parsed_data = self.api_call(sentence, properties=default_properties)
+
+            assert len(parsed_data['sentences']) == 1
+
+            for parse in parsed_data['sentences']:
+                tree = self.make_tree(parse)
+                yield iter([tree])
+
+    def parse_text(self, text, *args, **kwargs):
+        """Parse a piece of text.
+
+        The text might contain several sentences which will be split by CoreNLP.
+
+        :param str text: text to be split.
+        :returns: an iterable of syntactic structures.  # TODO: should it be an iterable of iterables?
+
+        """
+        parsed_data = self.api_call(text, *args, **kwargs)
+
+        for parse in parsed_data['sentences']:
+            yield self.make_tree(parse)
+
+    def tokenize(self, text, properties=None):
+        """Tokenize a string of text.
+
+        >>> parser = CoreNLPParser(url='http://localhost:9000')
+
+        >>> text = 'Good muffins cost $3.88\\nin New York.  Please buy me\\ntwo of them.\\nThanks.'
+        >>> list(parser.tokenize(text))
+        ['Good', 'muffins', 'cost', '$', '3.88', 'in', 'New', 'York', '.', 'Please', 'buy', 'me', 'two', 'of', 'them', '.', 'Thanks', '.']
+
+        >>> s = "The colour of the wall is blue."
+        >>> list(
+        ...     parser.tokenize(
+        ...         'The colour of the wall is blue.',
+        ...             properties={'tokenize.options': 'americanize=true'},
+        ...     )
+        ... )
+        ['The', 'color', 'of', 'the', 'wall', 'is', 'blue', '.']
+
+        """
+        default_properties = {
+            'annotators': 'tokenize,ssplit',
+        }
+
+        default_properties.update(properties or {})
+
+        result = self.api_call(text, properties=default_properties)
+
+        for sentence in result['sentences']:
+            for token in sentence['tokens']:
+                yield token['originalText']
+
+
+class CoreNLPParser(GenericCoreNLPParser):
+    """
+    >>> parser = CoreNLPParser(url='http://localhost:9000')
+
+    >>> next(
+    ...     parser.raw_parse('The quick brown fox jumps over the lazy dog.')
+    ... ).pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+                         ROOT
+                          |
+                          S
+           _______________|__________________________
+          |                         VP               |
+          |                _________|___             |
+          |               |             PP           |
+          |               |     ________|___         |
+          NP              |    |            NP       |
+      ____|__________     |    |     _______|____    |
+     DT   JJ    JJ   NN  VBZ   IN   DT      JJ   NN  .
+     |    |     |    |    |    |    |       |    |   |
+    The quick brown fox jumps over the     lazy dog  .
+
+    >>> (parse_fox, ), (parse_wolf, ) = parser.raw_parse_sents(
+    ...     [
+    ...         'The quick brown fox jumps over the lazy dog.',
+    ...         'The quick grey wolf jumps over the lazy fox.',
+    ...     ]
+    ... )
+
+    >>> parse_fox.pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+                         ROOT
+                          |
+                          S
+           _______________|__________________________
+          |                         VP               |
+          |                _________|___             |
+          |               |             PP           |
+          |               |     ________|___         |
+          NP              |    |            NP       |
+      ____|__________     |    |     _______|____    |
+     DT   JJ    JJ   NN  VBZ   IN   DT      JJ   NN  .
+     |    |     |    |    |    |    |       |    |   |
+    The quick brown fox jumps over the     lazy dog  .
+
+    >>> parse_wolf.pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+                         ROOT
+                          |
+                          S
+           _______________|__________________________
+          |                         VP               |
+          |                _________|___             |
+          |               |             PP           |
+          |               |     ________|___         |
+          NP              |    |            NP       |
+      ____|_________      |    |     _______|____    |
+     DT   JJ   JJ   NN   VBZ   IN   DT      JJ   NN  .
+     |    |    |    |     |    |    |       |    |   |
+    The quick grey wolf jumps over the     lazy fox  .
+
+    >>> (parse_dog, ), (parse_friends, ) = parser.parse_sents(
+    ...     [
+    ...         "I 'm a dog".split(),
+    ...         "This is my friends ' cat ( the tabby )".split(),
+    ...     ]
+    ... )
+
+    >>> parse_dog.pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+            ROOT
+             |
+             S
+      _______|____
+     |            VP
+     |    ________|___
+     NP  |            NP
+     |   |         ___|___
+    PRP VBP       DT      NN
+     |   |        |       |
+     I   'm       a      dog
+
+    >>> parse_friends.pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+         ROOT
+          |
+          S
+      ____|___________
+     |                VP
+     |     ___________|_____________
+     |    |                         NP
+     |    |                  _______|_________
+     |    |                 NP               PRN
+     |    |            _____|_______      ____|______________
+     NP   |           NP            |    |        NP         |
+     |    |     ______|_________    |    |     ___|____      |
+     DT  VBZ  PRP$   NNS       POS  NN -LRB-  DT       NN  -RRB-
+     |    |    |      |         |   |    |    |        |     |
+    This  is   my  friends      '  cat -LRB- the     tabby -RRB-
+
+    >>> parse_john, parse_mary, = parser.parse_text(
+    ...     'John loves Mary. Mary walks.'
+    ... )
+
+    >>> parse_john.pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+          ROOT
+           |
+           S
+      _____|_____________
+     |          VP       |
+     |      ____|___     |
+     NP    |        NP   |
+     |     |        |    |
+    NNP   VBZ      NNP   .
+     |     |        |    |
+    John loves     Mary  .
+
+    >>> parse_mary.pretty_print()  # doctest: +NORMALIZE_WHITESPACE
+          ROOT
+           |
+           S
+      _____|____
+     NP    VP   |
+     |     |    |
+    NNP   VBZ   .
+     |     |    |
+    Mary walks  .
+
+    Special cases
+    -------------
+
+    >>> next(
+    ...     parser.raw_parse(
+    ...         'NASIRIYA, Iraq—Iraqi doctors who treated former prisoner of war '
+    ...         'Jessica Lynch have angrily dismissed claims made in her biography '
+    ...         'that she was raped by her Iraqi captors.'
+    ...     )
+    ... ).height()
+    20
+
+    >>> next(
+    ...     parser.raw_parse(
+    ...         "The broader Standard & Poor's 500 Index <.SPX> was 0.46 points lower, or "
+    ...         '0.05 percent, at 997.02.'
+    ...     )
+    ... ).height()
+    9
+
+    """
+
+    _OUTPUT_FORMAT = 'penn'
+    parser_annotator = 'parse'
+
+    def make_tree(self, result):
+        return Tree.fromstring(result['parse'])
+
+
+class CoreNLPDependencyParser(GenericCoreNLPParser):
+    """Dependency parser.
+
+    >>> dep_parser = CoreNLPDependencyParser(url='http://localhost:9000')
+
+    >>> parse, = dep_parser.raw_parse(
+    ...     'The quick brown fox jumps over the lazy dog.'
+    ... )
+    >>> print(parse.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    The     DT      4       det
+    quick   JJ      4       amod
+    brown   JJ      4       amod
+    fox     NN      5       nsubj
+    jumps   VBZ     0       ROOT
+    over    IN      9       case
+    the     DT      9       det
+    lazy    JJ      9       amod
+    dog     NN      5       nmod
+    .       .       5       punct
+
+    >>> print(parse.tree())  # doctest: +NORMALIZE_WHITESPACE
+    (jumps (fox The quick brown) (dog over the lazy) .)
+
+    >>> for governor, dep, dependent in parse.triples():
+    ...     print(governor, dep, dependent)  # doctest: +NORMALIZE_WHITESPACE
+        ('jumps', 'VBZ') nsubj ('fox', 'NN')
+        ('fox', 'NN') det ('The', 'DT')
+        ('fox', 'NN') amod ('quick', 'JJ')
+        ('fox', 'NN') amod ('brown', 'JJ')
+        ('jumps', 'VBZ') nmod ('dog', 'NN')
+        ('dog', 'NN') case ('over', 'IN')
+        ('dog', 'NN') det ('the', 'DT')
+        ('dog', 'NN') amod ('lazy', 'JJ')
+        ('jumps', 'VBZ') punct ('.', '.')
+
+    >>> (parse_fox, ), (parse_dog, ) = dep_parser.raw_parse_sents(
+    ...     [
+    ...         'The quick brown fox jumps over the lazy dog.',
+    ...         'The quick grey wolf jumps over the lazy fox.',
+    ...     ]
+    ... )
+    >>> print(parse_fox.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    The DT      4       det
+    quick       JJ      4       amod
+    brown       JJ      4       amod
+    fox NN      5       nsubj
+    jumps       VBZ     0       ROOT
+    over        IN      9       case
+    the DT      9       det
+    lazy        JJ      9       amod
+    dog NN      5       nmod
+    .   .       5       punct
+
+    >>> print(parse_dog.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    The DT      4       det
+    quick       JJ      4       amod
+    grey        JJ      4       amod
+    wolf        NN      5       nsubj
+    jumps       VBZ     0       ROOT
+    over        IN      9       case
+    the DT      9       det
+    lazy        JJ      9       amod
+    fox NN      5       nmod
+    .   .       5       punct
+
+    >>> (parse_dog, ), (parse_friends, ) = dep_parser.parse_sents(
+    ...     [
+    ...         "I 'm a dog".split(),
+    ...         "This is my friends ' cat ( the tabby )".split(),
+    ...     ]
+    ... )
+    >>> print(parse_dog.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    I   PRP     4       nsubj
+    'm  VBP     4       cop
+    a   DT      4       det
+    dog NN      0       ROOT
+
+    >>> print(parse_friends.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    This        DT      6       nsubj
+    is  VBZ     6       cop
+    my  PRP$    4       nmod:poss
+    friends     NNS     6       nmod:poss
+    '   POS     4       case
+    cat NN      0       ROOT
+    -LRB-       -LRB-   9       punct
+    the DT      9       det
+    tabby       NN      6       appos
+    -RRB-       -RRB-   9       punct
+
+    >>> parse_john, parse_mary, = dep_parser.parse_text(
+    ...     'John loves Mary. Mary walks.'
+    ... )
+
+    >>> print(parse_john.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    John        NNP     2       nsubj
+    loves       VBZ     0       ROOT
+    Mary        NNP     2       dobj
+    .   .       2       punct
+
+    >>> print(parse_mary.to_conll(4))  # doctest: +NORMALIZE_WHITESPACE
+    Mary        NNP     2       nsubj
+    walks       VBZ     0       ROOT
+    .   .       2       punct
+
+    Special cases
+    -------------
+
+    Non-breaking space inside of a token.
+
+    >>> len(
+    ...     next(
+    ...         dep_parser.raw_parse(
+    ...             'Anhalt said children typically treat a 20-ounce soda bottle as one '
+    ...             'serving, while it actually contains 2 1/2 servings.'
+    ...         )
+    ...     ).nodes
+    ... )
+    21
+
+    Phone  numbers.
+
+    >>> len(
+    ...     next(
+    ...         dep_parser.raw_parse('This is not going to crash: 01 111 555.')
+    ...     ).nodes
+    ... )
+    10
+
+    """
+
+    _OUTPUT_FORMAT = 'conll2007'
+    parser_annotator = 'depparse'
+
+    def make_tree(self, result):
+
+        return DependencyGraph(
+            (
+                ' '.join(n_items[1:])  # NLTK expects an iterable of strings...
+                for n_items in sorted(transform(result))
+            ),
+            cell_separator=' ',  # To make sure that a non-breaking space is kept inside of a token.
+        )
+
+
+def transform(sentence):
+    for dependency in sentence['basicDependencies']:
+
+        dependent_index = dependency['dependent']
+        token = sentence['tokens'][dependent_index - 1]
+
+        # Return values that we don't know as '_'. Also, consider tag and ctag
+        # to be equal.
+        yield (
+            dependent_index,
+            '_',
+            token['word'],
+            token['lemma'],
+            token['pos'],
+            token['pos'],
+            '_',
+            str(dependency['governor']),
+            dependency['dep'],
+            '_',
+            '_',
+        )
+
+
+def setup_module(module):
+    from nose import SkipTest
+
+    global server
+    try:
+        server = CoreNLPServer(port=9000)
+    except LookupError as e:
+        raise SkipTest('Could not instantiate CoreNLPServer.')
+
+    try:
+        server.start()
+    except CoreNLPServerError as e:
+        raise SkipTest(
+            'Skipping CoreNLP tests because the server could not be started. '
+            'Make sure that the 9000 port is free. '
+            '{}'.format(e.strerror)
+        )
+
+
+def teardown_module(module):
+    server.stop()
diff --git a/setup.py b/setup.py
index 4686bdce5a..5022fcb853 100644
--- a/setup.py
+++ b/setup.py
@@ -45,8 +45,11 @@
         'pyparsing',
     ],
     'twitter': [
-        'twython'
-    ]
+        'twython',
+    ],
+    'corenlp': [
+        'requests',
+    ],
 }
 
 # Add a group made up of all optional dependencies