diff --git a/chatterbot/__main__.py b/chatterbot/__main__.py
index 1fe45f7ef..d6c03a735 100644
--- a/chatterbot/__main__.py
+++ b/chatterbot/__main__.py
@@ -1,6 +1,5 @@
 import importlib
 import sys
-import os
 
 
 def get_chatterbot_version():
@@ -8,23 +7,6 @@ def get_chatterbot_version():
     return chatterbot.__version__
 
 
-def get_nltk_data_directories():
-    import nltk.data
-
-    data_directories = []
-
-    # Find each data directory in the NLTK path that has content
-    for path in nltk.data.path:
-        if os.path.exists(path):
-            if os.listdir(path):
-                data_directories.append(path)
-
-    return os.linesep.join(data_directories)
-
-
 if __name__ == '__main__':
     if '--version' in sys.argv:
         print(get_chatterbot_version())
-
-    if 'list_nltk_data' in sys.argv:
-        print(get_nltk_data_directories())
diff --git a/chatterbot/chatterbot.py b/chatterbot/chatterbot.py
index 19b33635c..054309543 100644
--- a/chatterbot/chatterbot.py
+++ b/chatterbot/chatterbot.py
@@ -54,31 +54,6 @@ def __init__(self, name, **kwargs):
         # Allow the bot to save input it receives so that it can learn
         self.read_only = kwargs.get('read_only', False)
 
-        if kwargs.get('initialize', True):
-            self.initialize()
-
-    def get_initialization_functions(self):
-        initialization_functions = set()
-
-        initialization_functions.update(utils.get_initialization_functions(
-            self, 'storage.tagger'
-        ))
-
-        for search_algorithm in self.search_algorithms.values():
-            search_algorithm_functions = utils.get_initialization_functions(
-                search_algorithm, 'compare_statements'
-            )
-            initialization_functions.update(search_algorithm_functions)
-
-        return initialization_functions
-
-    def initialize(self):
-        """
-        Do any work that needs to be done before the chatbot can process responses.
-        """
-        for function in self.get_initialization_functions():
-            function()
-
     def get_response(self, statement=None, **kwargs):
         """
         Return the bot's response based on the input.
diff --git a/chatterbot/storage/storage_adapter.py b/chatterbot/storage/storage_adapter.py
index cd8854b11..74750311a 100644
--- a/chatterbot/storage/storage_adapter.py
+++ b/chatterbot/storage/storage_adapter.py
@@ -1,6 +1,6 @@
 import logging
 from chatterbot import languages
-from chatterbot.tagging import PosHypernymTagger
+from chatterbot.tagging import PosLemmaTagger
 
 
 class StorageAdapter(object):
@@ -12,10 +12,12 @@ class StorageAdapter(object):
     def __init__(self, *args, **kwargs):
         """
         Initialize common attributes shared by all storage adapters.
+
+        :param str tagger_language: The language that the tagger uses to remove stopwords.
         """
         self.logger = kwargs.get('logger', logging.getLogger(__name__))
 
-        self.tagger = PosHypernymTagger(language=kwargs.get(
+        self.tagger = PosLemmaTagger(language=kwargs.get(
             'tagger_language', languages.ENG
         ))
 
diff --git a/chatterbot/tagging.py b/chatterbot/tagging.py
index cfd755ca2..3d73986af 100644
--- a/chatterbot/tagging.py
+++ b/chatterbot/tagging.py
@@ -1,10 +1,5 @@
 import string
 from chatterbot import languages
-from chatterbot import utils
-from chatterbot.tokenizers import get_sentence_tokenizer
-from nltk import pos_tag
-from nltk.corpus import wordnet, stopwords
-from nltk.corpus.reader.wordnet import WordNetError
 import spacy
 
 
@@ -56,143 +51,3 @@ def get_bigram_pair_string(self, text):
             ]
 
         return ' '.join(bigram_pairs)
-
-
-class PosHypernymTagger(object):
-    """
-    For each non-stopword in a string, return a string where each word is a
-    hypernym preceded by the part of speech of the word before it.
-    """
-
-    def __init__(self, language=None):
-        self.language = language or languages.ENG
-
-        self.sentence_tokenizer = None
-
-        self.stopwords = None
-
-        self.initialization_functions = [
-            utils.download_nltk_stopwords,
-            utils.download_nltk_wordnet,
-            utils.download_nltk_averaged_perceptron_tagger
-        ]
-
-    def get_stopwords(self):
-        """
-        Get the list of stopwords from the NLTK corpus.
-        """
-        if self.stopwords is None:
-            self.stopwords = stopwords.words(self.language.ENGLISH_NAME.lower())
-
-        return self.stopwords
-
-    def tokenize_sentence(self, sentence):
-        """
-        Tokenize the provided sentence.
-        """
-        if self.sentence_tokenizer is None:
-            self.sentence_tokenizer = get_sentence_tokenizer(self.language)
-
-        return self.sentence_tokenizer.tokenize(sentence)
-
-    def stem_words(self, words):
-        """
-        Return the first character of the word in place of a part-of-speech tag.
-        """
-        return [
-            (word, word.lower()[0], ) for word in words
-        ]
-
-    def get_pos_tags(self, words):
-        try:
-            # pos_tag supports eng and rus
-            tags = pos_tag(words, lang=self.language.ISO_639)
-        except NotImplementedError:
-            tags = self.stem_words(words)
-        except LookupError:
-            tags = self.stem_words(words)
-
-        return tags
-
-    def get_hypernyms(self, pos_tags):
-        """
-        Return the hypernyms for each word in a list of POS tagged words.
-        """
-        results = []
-
-        for word, pos in pos_tags:
-            try:
-                synsets = wordnet.synsets(word, utils.treebank_to_wordnet(pos), lang=self.language.ISO_639)
-            except WordNetError:
-                synsets = None
-            except LookupError:
-                # Don't return any synsets if the language is not supported
-                synsets = None
-
-            if synsets:
-                synset = synsets[0]
-                hypernyms = synset.hypernyms()
-
-                if hypernyms:
-                    results.append(hypernyms[0].name().split('.')[0])
-                else:
-                    results.append(word)
-            else:
-                results.append(word)
-
-        return results
-
-    def get_bigram_pair_string(self, text):
-        """
-        For example:
-        What a beautiful swamp
-
-        becomes:
-
-        DT:beautiful JJ:wetland
-        """
-        WORD_INDEX = 0
-        POS_INDEX = 1
-
-        pos_tags = []
-
-        for sentence in self.tokenize_sentence(text.strip()):
-
-            # Remove punctuation
-            if sentence and sentence[-1] in string.punctuation:
-                sentence_with_punctuation_removed = sentence[:-1]
-
-                if sentence_with_punctuation_removed:
-                    sentence = sentence_with_punctuation_removed
-
-            words = sentence.split()
-
-            pos_tags.extend(self.get_pos_tags(words))
-
-        hypernyms = self.get_hypernyms(pos_tags)
-
-        high_quality_bigrams = []
-        all_bigrams = []
-
-        word_count = len(pos_tags)
-
-        if word_count == 1:
-            all_bigrams.append(
-                pos_tags[0][WORD_INDEX].lower()
-            )
-
-        for index in range(1, word_count):
-            word = pos_tags[index][WORD_INDEX].lower()
-            previous_word_pos = pos_tags[index - 1][POS_INDEX]
-            if word not in self.get_stopwords() and len(word) > 1:
-                bigram = previous_word_pos + ':' + hypernyms[index].lower()
-                high_quality_bigrams.append(bigram)
-                all_bigrams.append(bigram)
-            else:
-                bigram = previous_word_pos + ':' + word
-                all_bigrams.append(bigram)
-
-        if high_quality_bigrams:
-            all_bigrams = high_quality_bigrams
-
-        return ' '.join(all_bigrams)
diff --git a/chatterbot/tokenizers.py b/chatterbot/tokenizers.py
deleted file mode 100644
index ab1f27d0e..000000000
--- a/chatterbot/tokenizers.py
+++ /dev/null
@@ -1,62 +0,0 @@
-from pickle import dump, load
-from nltk.tokenize.punkt import PunktSentenceTokenizer, PunktTrainer
-from nltk.tokenize import _treebank_word_tokenizer
-from chatterbot.corpus import load_corpus, list_corpus_files
-from chatterbot import languages
-
-
-def get_sentence_tokenizer(language):
-    """
-    Return the sentence tokenizer callable.
-    """
-
-    pickle_path = 'sentence_tokenizer.pickle'
-
-    try:
-        input_file = open(pickle_path, 'rb')
-        sentence_tokenizer = load(input_file)
-        input_file.close()
-    except FileNotFoundError:
-
-        data_file_paths = []
-
-        sentences = []
-
-        try:
-            # Get the paths to each file the bot will be trained with
-            corpus_files = list_corpus_files('chatterbot.corpus.{language}'.format(
-                language=language.ENGLISH_NAME.lower()
-            ))
-        except LookupError:
-            # Fall back to English sentence splitting rules if a language is not supported
-            corpus_files = list_corpus_files('chatterbot.corpus.{language}'.format(
-                language=languages.ENG.ENGLISH_NAME.lower()
-            ))
-
-        data_file_paths.extend(corpus_files)
-
-        for corpus, _categories, _file_path in load_corpus(*data_file_paths):
-            for conversation in corpus:
-                for text in conversation:
-                    sentences.append(text.upper())
-                    sentences.append(text.lower())
-
-        trainer = PunktTrainer()
-        trainer.INCLUDE_ALL_COLLOCS = True
-        trainer.train('\n'.join(sentences))
-
-        sentence_tokenizer = PunktSentenceTokenizer(trainer.get_params())
-
-        # Pickle the sentence tokenizer for future use
-        output_file = open(pickle_path, 'wb')
-        dump(sentence_tokenizer, output_file, -1)
-        output_file.close()
-
-    return sentence_tokenizer
-
-
-def get_word_tokenizer(language):
-    """
-    Return the word tokenizer callable.
-    """
-    return _treebank_word_tokenizer
diff --git a/chatterbot/trainers.py b/chatterbot/trainers.py
index d5cc08a38..48d2ab7ce 100644
--- a/chatterbot/trainers.py
+++ b/chatterbot/trainers.py
@@ -2,10 +2,9 @@
 import sys
 import csv
 import time
-from multiprocessing import Pool, Manager
 from dateutil import parser as date_parser
 from chatterbot.conversation import Statement
-from chatterbot.tagging import PosHypernymTagger
+from chatterbot.tagging import PosLemmaTagger
 from chatterbot import utils
 
 
@@ -17,8 +16,6 @@ class Trainer(object):
            trainer. The environment variable ``CHATTERBOT_SHOW_TRAINING_PROGRESS``
            can also be set to control this. ``show_training_progress`` will override
            the environment variable if it is set.
-
-    :param str tagger_language: The language that the tagger uses to remove stopwords.
     """
 
     def __init__(self, chatbot, **kwargs):
@@ -176,41 +173,6 @@ def train(self, *corpus_paths):
             self.chatbot.storage.create_many(statements_to_create)
 
 
-def read_file(files, queue, preprocessors, tagger):
-
-    statements_from_file = []
-
-    for tsv_file in files:
-        with open(tsv_file, 'r', encoding='utf-8') as tsv:
-            reader = csv.reader(tsv, delimiter='\t')
-
-            previous_statement_text = None
-            previous_statement_search_text = ''
-
-            for row in reader:
-                if len(row) > 0:
-                    statement = Statement(
-                        text=row[3],
-                        in_response_to=previous_statement_text,
-                        conversation='training',
-                        created_at=date_parser.parse(row[0]),
-                        persona=row[1]
-                    )
-
-                    for preprocessor in preprocessors:
-                        statement = preprocessor(statement)
-
-                    statement.search_text = tagger.get_bigram_pair_string(statement.text)
-                    statement.search_in_response_to = previous_statement_search_text
-
-                    previous_statement_text = statement.text
-                    previous_statement_search_text = statement.search_text
-
-                    statements_from_file.append(statement)
-
-    queue.put(tuple(statements_from_file))
-
-
 class UbuntuCorpusTrainer(Trainer):
     """
     Allow chatbots to be trained with the data from the Ubuntu Dialog Corpus.
@@ -325,7 +287,7 @@ def track_progress(members):
     def train(self):
         import glob
 
-        tagger = PosHypernymTagger(language=self.chatbot.storage.tagger.language)
+        tagger = PosLemmaTagger(language=self.chatbot.storage.tagger.language)
 
         # Download and extract the Ubuntu dialog corpus if needed
         corpus_download_path = self.download(self.data_download_url)
@@ -339,9 +301,6 @@ def train(self):
             '**', '**', '*.tsv'
         )
 
-        manager = Manager()
-        queue = manager.Queue()
-
         def chunks(items, items_per_chunk):
             for start_index in range(0, len(items), items_per_chunk):
                 end_index = start_index + items_per_chunk
@@ -351,55 +310,40 @@ def chunks(items, items_per_chunk):
 
         file_groups = tuple(chunks(file_list, 10000))
 
-        argument_groups = tuple(
-            (
-                file_names,
-                queue,
-                self.chatbot.preprocessors,
-                tagger,
-            ) for file_names in file_groups
-        )
-
-        pool_batches = chunks(argument_groups, 9)
-
-        total_batches = len(file_groups)
-        batch_number = 0
-
         start_time = time.time()
 
-        with Pool() as pool:
-            for pool_batch in pool_batches:
-                pool.starmap(read_file, pool_batch)
+        for tsv_files in file_groups:
+
+            statements_from_file = []
 
-                while True:
+            for tsv_file in tsv_files:
+                with open(tsv_file, 'r', encoding='utf-8') as tsv:
+                    reader = csv.reader(tsv, delimiter='\t')
 
-                    if queue.empty():
-                        break
+                    previous_statement_text = None
+                    previous_statement_search_text = ''
 
-                    batch_number += 1
+                    for row in reader:
+                        if len(row) > 0:
+                            statement = Statement(
+                                text=row[3],
+                                in_response_to=previous_statement_text,
+                                conversation='training',
+                                created_at=date_parser.parse(row[0]),
+                                persona=row[1]
+                            )
 
-                    print('Training with batch {} with {} batches remaining...'.format(
-                        batch_number,
-                        total_batches - batch_number
-                    ))
+                            for preprocessor in self.chatbot.preprocessors:
+                                statement = preprocessor(statement)
 
-                    self.chatbot.storage.create_many(queue.get())
+                            statement.search_text = tagger.get_bigram_pair_string(statement.text)
+                            statement.search_in_response_to = previous_statement_search_text
 
-                elapsed_time = time.time() - start_time
-                time_per_batch = elapsed_time / batch_number
-                remaining_time = time_per_batch * (total_batches - batch_number)
+                            previous_statement_text = statement.text
+                            previous_statement_search_text = statement.search_text
 
-                print('{:.0f} hours {:.0f} minutes {:.0f} seconds elapsed.'.format(
-                    elapsed_time // 3600 % 24,
-                    elapsed_time // 60 % 60,
-                    elapsed_time % 60
-                ))
+                            statements_from_file.append(statement)
 
-                print('{:.0f} hours {:.0f} minutes {:.0f} seconds remaining.'.format(
-                    remaining_time // 3600 % 24,
-                    remaining_time // 60 % 60,
-                    remaining_time % 60
-                ))
-                print('---')
+            self.chatbot.storage.create_many(statements_from_file)
 
         print('Training took', time.time() - start_time, 'seconds.')
diff --git a/chatterbot/utils.py b/chatterbot/utils.py
index 95dada105..61c27a0f6 100644
--- a/chatterbot/utils.py
+++ b/chatterbot/utils.py
@@ -1,7 +1,6 @@
 """
 ChatterBot utility functions
 """
-from nltk.corpus import wordnet
 
 
 def import_module(dotted_path):
@@ -18,19 +17,6 @@ def import_module(dotted_path):
     return getattr(module, module_parts[-1])
 
 
-def get_initialization_functions(obj, attribute):
-    """
-    Return all initialization methods for the comparison algorithm.
-    Initialization methods must start with 'initialize_' and take no parameters.
-    """
-    attribute_parts = attribute.split('.')
-    outermost_attribute = getattr(obj, attribute_parts.pop(0))
-    for next_attribute in attribute_parts:
-        outermost_attribute = getattr(outermost_attribute, next_attribute)
-
-    return getattr(outermost_attribute, 'initialization_functions', [])
-
-
 def initialize_class(data, *args, **kwargs):
     """
     :param data: A string or dictionary containing a import_path attribute.
@@ -84,56 +70,6 @@ def validate_adapter_class(validate_class, adapter_class):
         )
 
 
-def nltk_download_corpus(resource_path):
-    """
-    Download the specified NLTK corpus file
-    unless it has already been downloaded.
-
-    Returns True if the corpus needed to be downloaded.
-    """
-    from nltk.data import find
-    from nltk import download
-    from os.path import split, sep
-    from zipfile import BadZipfile
-
-    # Download the NLTK data only if it is not already downloaded
-    _, corpus_name = split(resource_path)
-
-    if not resource_path.endswith(sep):
-        resource_path = resource_path + sep
-
-    downloaded = False
-
-    try:
-        find(resource_path)
-    except LookupError:
-        download(corpus_name)
-        downloaded = True
-    except BadZipfile:
-        raise BadZipfile(
-            'The NLTK corpus file being opened is not a zipfile, '
-            'or it has been corrupted and needs to be manually deleted.'
-        )
-
-    return downloaded
-
-
-def treebank_to_wordnet(pos):
-    """
-    Convert Treebank part-of-speech tags to Wordnet part-of-speech tags.
-    * https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html
-    * http://www.nltk.org/_modules/nltk/corpus/reader/wordnet.html
-    """
-    data_map = {
-        'N': wordnet.NOUN,
-        'J': wordnet.ADJ,
-        'V': wordnet.VERB,
-        'R': wordnet.ADV
-    }
-
-    return data_map.get(pos[0])
-
-
 def get_response_time(chatbot, statement='Hello'):
     """
     Returns the amount of time taken for a given
@@ -181,25 +117,3 @@ def print_progress_bar(description, iteration_counter, total_items, progress_bar
     sys.stdout.flush()
     if total_items == iteration_counter:
         print('\r')
-
-
-def download_nltk_stopwords():
-    """
-    Download required NLTK stopwords corpus if it has not already been downloaded.
-    """
-    nltk_download_corpus('stopwords')
-
-
-def download_nltk_wordnet():
-    """
-    Download required NLTK corpora if they have not already been downloaded.
-    """
-    nltk_download_corpus('corpora/wordnet')
-
-
-def download_nltk_averaged_perceptron_tagger():
-    """
-    Download the NLTK averaged perceptron tagger that is required for this algorithm
-    to run only if the corpora has not already been downloaded.
-    """
-    nltk_download_corpus('averaged_perceptron_tagger')
diff --git a/docs/commands.rst b/docs/commands.rst
index 9792848a6..0a2e69dea 100644
--- a/docs/commands.rst
+++ b/docs/commands.rst
@@ -13,15 +13,3 @@ you have then you can run the following command.
 .. code-block:: bash
 
    python -m chatterbot --version
-
-Locate NLTK data
-=================
-
-ChatterBot uses the Natural Language Toolkit (NLTK) for various
-language processing functions. ChatterBot downloads additional
-data that is required by NLTK. The following command can be used
-to find all NLTK data directories that contain files.
-
-.. code-block:: bash
-
-   python -m chatterbot list_nltk_data
diff --git a/docs/utils.rst b/docs/utils.rst
index 463b7ff4a..e8bd9e965 100644
--- a/docs/utils.rst
+++ b/docs/utils.rst
@@ -18,11 +18,6 @@ Class initialization
 .. autofunction:: chatterbot.utils.initialize_class
 
 
-NLTK corpus downloader
-
-.. autofunction:: chatterbot.utils.nltk_download_corpus
-
-
 ChatBot response time
 ---------------------
 
diff --git a/tests/base_case.py b/tests/base_case.py
index 05137f2ac..f9b7c1d24 100644
--- a/tests/base_case.py
+++ b/tests/base_case.py
@@ -1,17 +1,10 @@
 from unittest import TestCase, SkipTest
 from chatterbot import ChatBot
-from chatterbot import utils
 
 
 class ChatBotTestCase(TestCase):
 
     def setUp(self):
-
-        # Make sure that test requirements are downloaded
-        utils.download_nltk_stopwords()
-        utils.download_nltk_wordnet()
-        utils.download_nltk_averaged_perceptron_tagger()
-
         self.chatbot = ChatBot('Test Bot', **self.get_kwargs())
 
     def tearDown(self):
diff --git a/tests/test_chatbot.py b/tests/test_chatbot.py
index 790c5a487..dd990fdd6 100644
--- a/tests/test_chatbot.py
+++ b/tests/test_chatbot.py
@@ -37,45 +37,6 @@ def test_in_response_to_provided(self):
         )
         self.assertIsNotNone(statement)
 
-    def test_get_initialization_functions(self):
-        """
-        Test that the initialization functions are returned.
-        """
-        functions = self.chatbot.get_initialization_functions()
-
-        self.assertIn('download_nltk_stopwords', str(functions))
-        self.assertIn('download_nltk_wordnet', str(functions))
-        self.assertIn('download_nltk_averaged_perceptron_tagger', str(functions))
-        self.assertIsLength(functions, 3)
-
-    def test_get_initialization_functions_spacy_similarity(self):
-        """
-        Test that the initialization functions are returned.
-        """
-        from chatterbot.comparisons import spacy_similarity
-
-        list(self.chatbot.search_algorithms.values())[0].compare_statements = spacy_similarity
-        functions = self.chatbot.get_initialization_functions()
-
-        self.assertIn('download_nltk_stopwords', str(functions))
-        self.assertIn('download_nltk_wordnet', str(functions))
-        self.assertIn('download_nltk_averaged_perceptron_tagger', str(functions))
-        self.assertIsLength(functions, 3)
-
-    def test_get_initialization_functions_jaccard_similarity(self):
-        """
-        Test that the initialization functions are returned.
-        """
-        from chatterbot.comparisons import jaccard_similarity
-
-        list(self.chatbot.search_algorithms.values())[0].compare_statements = jaccard_similarity
-        functions = self.chatbot.get_initialization_functions()
-
-        self.assertIn('download_nltk_wordnet', str(functions))
-        self.assertIn('download_nltk_stopwords', str(functions))
-        self.assertIn('download_nltk_averaged_perceptron_tagger', str(functions))
-        self.assertIsLength(functions, 3)
-
     def test_no_statements_known(self):
         """
         If there is no statements in the database, then the
@@ -352,9 +313,8 @@ def test_search_text_results_after_training(self):
             )
         ))
 
+        self.assertEqual(len(results), 1)
         self.assertEqual('Example A for search.', results[0].text)
-        self.assertEqual('Example B for search.', results[1].text)
-        self.assertIsLength(results, 2)
 
 
 class TestAdapterA(LogicAdapter):
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 62e19be59..b6720be3e 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -11,7 +11,3 @@ class CommandLineInterfaceTests(TestCase):
     def test_get_chatterbot_version(self):
         version = main.get_chatterbot_version()
         self.assertEqual(version, __version__)
-
-    def test_get_nltk_data_directories(self):
-        directories = main.get_nltk_data_directories()
-        self.assertIn('/', directories)
diff --git a/tests/test_search.py b/tests/test_search.py
index f51d18b48..6dcf3b2f7 100644
--- a/tests/test_search.py
+++ b/tests/test_search.py
@@ -78,14 +78,9 @@ def test_get_closest_statement(self):
         statement = Statement(text='This is a lovely swamp.')
         results = list(self.search_algorithm.search(statement))
 
-        self.assertIsLength(results, 2)
-
-        results_text = [result.text for result in results]
-
-        self.assertIn('This is a lovely bog.', results_text)
-        self.assertIn('This is a beautiful swamp.', results_text)
+        self.assertIsLength(results, 1)
+        self.assertEqual(results[0].text, 'This is a beautiful swamp.')
         self.assertGreater(results[0].confidence, 0)
-        self.assertGreater(results[1].confidence, 0)
 
     def test_different_punctuation(self):
         self.chatbot.storage.create_many([
@@ -97,8 +92,9 @@ def test_different_punctuation(self):
         statement = Statement(text='Are you good')
         results = list(self.search_algorithm.search(statement))
 
-        self.assertIsLength(results, 1)
-        self.assertEqual(results[0].text, 'Are you good?')
+        self.assertEqual(len(results), 2, msg=[r.search_text for r in results])
+        # Note: the last statement in the list always has the highest confidence
+        self.assertEqual(results[-1].text, 'Are you good?')
 
 
 class SearchComparisonFunctionLevenshteinDistanceComparisonTests(ChatBotTestCase):
@@ -117,23 +113,22 @@ def setUp(self):
     def test_get_closest_statement(self):
         """
         Note, the content of the in_response_to field for each of the
-        test statements is only required because the logic adapter will
-        filter out any statements that are not in response to a known statement.
+        test statements is only required because the search process will
+        filter out any statements that are not in response to something.
         """
         self.chatbot.storage.create_many([
-            Statement(text='Who do you love?', in_response_to='I hear you are going on a quest?'),
-            Statement(text='What is the meaning of life?', in_response_to='Yuck, black licorice jelly beans.'),
-            Statement(text='I am Iron Man.', in_response_to='What... is your quest?'),
-            Statement(text='What... is your quest?', in_response_to='I am Iron Man.'),
-            Statement(text='Yuck, black licorice jelly beans.', in_response_to='What is the meaning of life?'),
-            Statement(text='I hear you are going on a quest?', in_response_to='Who do you love?'),
+            Statement(text='What is the meaning of life?', in_response_to='...'),
+            Statement(text='I am Iron Man.', in_response_to='...'),
+            Statement(text='What... is your quest?', in_response_to='...'),
+            Statement(text='Yuck, black licorice jelly beans.', in_response_to='...'),
+            Statement(text='I hear you are going on a quest?', in_response_to='...'),
         ])
 
         statement = Statement(text='What is your quest?')
 
         results = list(self.search_algorithm.search(statement))
 
-        self.assertIsLength(results, 1)
+        self.assertEqual(len(results), 1, msg=[r.text for r in results])
         self.assertEqual(results[0].text, 'What... is your quest?')
 
     def test_confidence_exact_match(self):
diff --git a/tests/test_tagging.py b/tests/test_tagging.py
index b54bbca09..864dda607 100644
--- a/tests/test_tagging.py
+++ b/tests/test_tagging.py
@@ -1,7 +1,6 @@
 from unittest import TestCase
 from chatterbot import languages
 from chatterbot import tagging
-from chatterbot import utils
 
 
 class PosLemmaTaggerTests(TestCase):
@@ -136,152 +135,3 @@ def test_get_bigram_pair_string_two_character_words(self):
         )
 
         self.assertEqual(bigram_string, 'VERB:mu')
-
-
-class PosHypernymTaggerTests(TestCase):
-
-    def setUp(self):
-        self.tagger = tagging.PosHypernymTagger()
-
-        # Make sure the required NLTK data files are downloaded
-        for function in utils.get_initialization_functions(self, 'tagger'):
-            function()
-
-    def test_empty_string(self):
-        tagged_text = self.tagger.get_bigram_pair_string(
-            ''
-        )
-
-        self.assertEqual(tagged_text, '')
-
-    def test_tagging(self):
-        tagged_text = self.tagger.get_bigram_pair_string(
-            'Hello, how are you doing on this awesome day?'
-        )
-
-        self.assertEqual(tagged_text, 'DT:awesome JJ:time_unit')
-
-    def test_tagging_english(self):
-        self.tagger = tagging.PosHypernymTagger(
-            language=languages.ENG
-        )
-
-        tagged_text = self.tagger.get_bigram_pair_string(
-            'Hello, how are you doing on this awesome day?'
-        )
-
-        self.assertEqual(tagged_text, 'DT:awesome JJ:time_unit')
-
-    def test_tagging_french(self):
-        self.tagger = tagging.PosHypernymTagger(
-            language=languages.FRE
-        )
-
-        tagged_text = self.tagger.get_bigram_pair_string(
-            'Salut comment allez-vous?'
-        )
-
-        self.assertEqual(tagged_text, 's:comment c:allez-vous')
-
-    def test_tagging_russian(self):
-        self.tagger = tagging.PosHypernymTagger(
-            language=languages.RUS
-        )
-
-        tagged_text = self.tagger.get_bigram_pair_string(
-            'Привет, как ты?'
-        )
-
-        self.assertEqual(tagged_text, 'п:как к:ты')
-
-    def test_string_becomes_lowercase(self):
-        tagged_text = self.tagger.get_bigram_pair_string('THIS IS HOW IT BEGINS!')
-
-        self.assertEqual(tagged_text, 'NNP:begins')
-
-    def test_tagging_medium_sized_words(self):
-        tagged_text = self.tagger.get_bigram_pair_string('Hello, my name is Gunther.')
-
-        self.assertEqual(tagged_text, 'PRP$:language_unit VBZ:gunther')
-
-    def test_tagging_long_words(self):
-        tagged_text = self.tagger.get_bigram_pair_string('I play several orchestra instruments for pleasuer.')
-
-        self.assertEqual(tagged_text, 'PRP:compete VBP:several JJ:orchestra JJ:device IN:pleasuer')
-
-    def test_get_bigram_pair_string_punctuation_only(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            '?'
-        )
-
-        self.assertEqual(bigram_string, '?')
-
-    def test_get_bigram_pair_string_single_character(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            '🙂'
-        )
-
-        self.assertEqual(bigram_string, '🙂')
-
-    def test_get_bigram_pair_string_single_character_punctuated(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            '🤷?'
-        )
-
-        self.assertEqual(bigram_string, '🤷')
-
-    def test_get_bigram_pair_string_two_characters(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'AB'
-        )
-
-        self.assertEqual(bigram_string, 'ab')
-
-    def test_get_bigram_pair_string_three_characters(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'ABC'
-        )
-
-        self.assertEqual(bigram_string, 'abc')
-
-    def test_get_bigram_pair_string_four_characters(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'ABCD'
-        )
-
-        self.assertEqual(bigram_string, 'abcd')
-
-    def test_get_bigram_pair_string_five_characters(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'ABCDE'
-        )
-
-        self.assertEqual(bigram_string, 'abcde')
-
-    def test_get_bigram_pair_string_single_word(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'Hello'
-        )
-
-        self.assertEqual(bigram_string, 'hello')
-
-    def test_get_bigram_pair_string_multiple_words(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'Hello Dr. Salazar. How are you today?'
-        )
-
-        self.assertEqual(bigram_string, 'NNP:scholar NNP:salazar PRP:present')
-
-    def test_get_bigram_pair_string_single_character_words(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'a e i o u'
-        )
-
-        self.assertEqual(bigram_string, 'DT:e NN:i NN:o VBP:u')
-
-    def test_get_bigram_pair_string_two_character_words(self):
-        bigram_string = self.tagger.get_bigram_pair_string(
-            'Lo my mu it is of us'
-        )
-
-        self.assertEqual(bigram_string, 'PRP$:letter IN:us')
diff --git a/tests/test_tokenizers.py b/tests/test_tokenizers.py
deleted file mode 100644
index 329ecc7ee..000000000
--- a/tests/test_tokenizers.py
+++ /dev/null
@@ -1,37 +0,0 @@
-from unittest import TestCase
-from chatterbot import languages
-from chatterbot.tokenizers import get_sentence_tokenizer, get_word_tokenizer
-
-
-class EnglishSentenceTokenizerTests(TestCase):
-
-    def setUp(self):
-        super().setUp()
-
-        self.tokenizer = get_sentence_tokenizer(languages.ENG)
-
-    def test_one_sentence(self):
-        tokens = self.tokenizer.tokenize('Hello, how are you?')
-
-        self.assertEqual(len(tokens), 1)
-        self.assertIn('Hello, how are you?', tokens)
-
-    def test_two_sentences(self):
-        tokens = self.tokenizer.tokenize('It is so nice out. Don\'t you think so?')
-
-        self.assertEqual(len(tokens), 2)
-        self.assertIn('It is so nice out.', tokens)
-        self.assertIn('Don\'t you think so?', tokens)
-
-
-class EnglishWordTokenizerTests(TestCase):
-
-    def setUp(self):
-        super().setUp()
-
-        self.tokenizer = get_word_tokenizer(languages.ENG)
-
-    def test_one_sentence(self):
-        tokens = self.tokenizer.tokenize('Hello, how are you?')
-
-        self.assertEqual(['Hello', ',', 'how', 'are', 'you', '?'], tokens)
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 2c5909e78..fd127d397 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -9,16 +9,6 @@ def test_import_module(self):
         datetime = utils.import_module('datetime.datetime')
         self.assertTrue(hasattr(datetime, 'now'))
 
-    def test_nltk_download_corpus(self):
-        downloaded = utils.nltk_download_corpus('wordnet')
-        self.assertTrue(downloaded)
-
-    def test_treebank_to_wordnet(self):
-        self.assertEqual(utils.treebank_to_wordnet('NNS'), 'n')
-
-    def test_treebank_to_wordnet_no_match(self):
-        self.assertEqual(utils.treebank_to_wordnet('XXX'), None)
-
 
 class UtilityChatBotTestCase(ChatBotTestCase):
 
diff --git a/tests/training/test_list_training.py b/tests/training/test_list_training.py
index aac778827..7a54f392f 100644
--- a/tests/training/test_list_training.py
+++ b/tests/training/test_list_training.py
@@ -84,7 +84,7 @@ def test_training_sets_search_text(self):
         ))
 
         self.assertIsLength(statements, 1)
-        self.assertEqual(statements[0].search_text, 'RB:kind PRP$:headdress')
+        self.assertEqual(statements[0].search_text, 'VERB:hat')
 
     def test_training_sets_search_in_response_to(self):
 
@@ -100,7 +100,7 @@ def test_training_sets_search_in_response_to(self):
         ))
 
         self.assertIsLength(statements, 1)
-        self.assertEqual(statements[0].search_in_response_to, 'PRP:kind PRP$:headdress')
+        self.assertEqual(statements[0].search_in_response_to, 'VERB:hat')
 
     def test_database_has_correct_format(self):
         """
diff --git a/tests/training/test_ubuntu_corpus_training.py b/tests/training/test_ubuntu_corpus_training.py
index d3e4af74f..b09987a07 100644
--- a/tests/training/test_ubuntu_corpus_training.py
+++ b/tests/training/test_ubuntu_corpus_training.py
@@ -176,7 +176,7 @@ def test_train_sets_search_text(self):
         results = list(self.chatbot.storage.filter(text='Is anyone there?'))
 
         self.assertEqual(len(results), 2)
-        self.assertEqual(results[0].search_text, 'VBZ:anyone')
+        self.assertEqual(results[0].search_text, 'VERB:anyone NOUN:there')
 
     def test_train_sets_search_in_response_to(self):
         """
@@ -190,7 +190,7 @@ def test_train_sets_search_in_response_to(self):
         results = list(self.chatbot.storage.filter(in_response_to='Is anyone there?'))
 
         self.assertEqual(len(results), 2)
-        self.assertEqual(results[0].search_in_response_to, 'VBZ:anyone')
+        self.assertEqual(results[0].search_in_response_to, 'VERB:anyone NOUN:there')
 
     def test_is_extracted(self):
         """
diff --git a/tests_django/base_case.py b/tests_django/base_case.py
index 0d239ed11..0572de82d 100644
--- a/tests_django/base_case.py
+++ b/tests_django/base_case.py
@@ -1,9 +1,9 @@
 from chatterbot import ChatBot
-from django.test import TestCase
+from django.test import TransactionTestCase
 from tests_django import test_settings
 
 
-class ChatterBotTestCase(TestCase):
+class ChatterBotTestCase(TransactionTestCase):
 
     def setUp(self):
         super().setUp()
diff --git a/tests_django/test_chatbot.py b/tests_django/test_chatbot.py
index c0016f845..3397fa89d 100644
--- a/tests_django/test_chatbot.py
+++ b/tests_django/test_chatbot.py
@@ -283,6 +283,27 @@ def test_search_text_results_after_training(self):
             )
         ))
 
+        self.assertEqual(len(results), 1, msg=[r.text for r in results])
+        self.assertEqual('Example A for search.', results[0].text)
+
+    def test_search_text_contains_results_after_training(self):
+        """
+        ChatterBot should return close matches to an input
+        string when filtering using the search_text parameter.
+        """
+        self.chatbot.storage.create_many([
+            Statement('Example A for search.'),
+            Statement('Another example.'),
+            Statement('Example B for search.'),
+            Statement(text='Another statement.'),
+        ])
+
+        results = list(self.chatbot.storage.filter(
+            search_text_contains=self.chatbot.storage.tagger.get_bigram_pair_string(
+                'Example A for search.'
+            )
+        ))
+
+        self.assertEqual(len(results), 2, msg=[r.text for r in results])
         self.assertEqual('Example A for search.', results[0].text)
         self.assertEqual('Example B for search.', results[1].text)
-        self.assertEqual(len(results), 2)
diff --git a/tox.ini b/tox.ini
index 1191c34c7..e6eed6dff 100644
--- a/tox.ini
+++ b/tox.ini
@@ -2,7 +2,7 @@
 skipsdist = True
 
 [testenv]
-passenv = DJANGO_SETTINGS_MODULE NLTK_DATA PYTHONPATH HOME DISPLAY
+passenv = DJANGO_SETTINGS_MODULE PYTHONPATH HOME DISPLAY
 setenv = PYTHONDONTWRITEBYTECODE=1
 deps =
   django111: Django>=1.11,<1.12