diff --git a/lib/CoNLL_Annotation.py b/lib/CoNLL_Annotation.py
new file mode 100644
index 0000000..02fae7d
--- /dev/null
+++ b/lib/CoNLL_Annotation.py
@@ -0,0 +1,218 @@
+from collections import defaultdict, OrderedDict
+import re
+
+# CoNLL-U Format - https://universaldependencies.org/format.html
+
+
+def get_token_type(type_str):
+    if type_str =="CoNLL09_Token":
+        return CoNLL09_Token
+    elif type_str == "RNNTagger_Token":
+        return RNNTagger_Token
+    elif type_str == "CoNLLUP_Token":
+        return CoNLLUP_Token
+    elif type_str == "TigerNew_Token":
+        return TigerNew_Token
+    else:
+        raise NotImplementedError(f"I don't know what to do with {type_str} token type!")
+
+
+class TigerNew_Token():
+    def __init__(self, raw_line, word_ix):
+        info = raw_line.split() # [FORM, XPOS]
+        self.info = info
+        self.id = word_ix + 1 # 1-based ID as in the CoNLL file
+        self.position = word_ix # 0-based position in sentence
+        self.word = info[0]
+        self.lemma = "_"
+        self.pos_universal = "_"
+        self.pos_tag = info[1]
+        self.detail_tag = "_"
+        self.head = "_"
+        self.dep_tag = "_"
+        self.blank = "_"
+        self.auto_score = "_"
+        
+    def get_info(self):
+        return [str(self.id), self.word, self.lemma, self.pos_universal, self.pos_tag, self.detail_tag,
+                str(self.head), self.dep_tag, self.blank, self.auto_score]
+
+    def get_conllU_line(self, separator="\t"):
+        info = self.get_info()
+        return separator.join(info)
+
+
+class RNNTagger_Token():
+    def __init__(self, raw_line, word_ix):
+        info = raw_line.split() # [FORM, XPOS.FEATS, LEMMA]
+        self.info = info
+        self.id = word_ix + 1 # 1-based ID as in the CoNLL file
+        self.position = word_ix # 0-based position in sentence
+        self.word = info[0]
+        self.lemma = info[2]
+        self.pos_universal = "_"
+        self.pos_tag, self.detail_tag = self._process_tag(info[1]) # 'NN.Gen.Sg.Fem'
+        self.head = "_"
+        self.dep_tag = "_"
+        self.blank = "_"
+        self.auto_score = "_"
+        
+    def _process_tag(self, tag):
+        if tag == "_" or "." not in tag: return tag, "_"
+        info = tag.split(".")
+        return info[0], "|".join(info[1:])
+        
+    def get_info(self):
+        return [str(self.id), self.word, self.lemma, self.pos_universal, self.pos_tag, self.detail_tag,
+                str(self.head), self.dep_tag, self.blank, self.auto_score]
+
+    def get_conllU_line(self, separator="\t"):
+        info = self.get_info()
+        return separator.join(info)
+
+
+class CoNLLUP_Token():
+    def __init__(self, raw_line, word_ix):
+        info = raw_line.split()
+        # print(info)
+        # [ID, FORM, LEMMA, UPOS, XPOS, FEATS, HEAD, DEPREL, DEPS, MISC]
+        # [11, Prügel, Prügel, NN, NN, _, _, _,	_, 1.000000]
+        self.info = info
+        self.id = info[0] # 1-based ID as in the CoNLL file
+        self.position = word_ix # 0-based position in sentence
+        self.word = info[1]
+        self.lemma = info[2]
+        self.pos_universal = info[3]
+        self.pos_tag = self._process_tag(info[4]) # 'XPOS=NE|Case=Nom|Gender=Masc|Number=Sing' TODO: Reuse MorphInfo in the self.detail_tag
+        self.detail_tag = info[5]
+        self.head = info[6]
+        self.dep_tag = info[7]
+        self.blank = info[8] # ???
+        self.auto_score = info[9]
+        
+    def _process_tag(self, tag):
+        if tag == "_" or "|" not in tag: return tag # The XPOS=NE|Case=Nom... is only for Turku!
+        info = tag.split("|")
+        info = [x.split("=") for x in info]
+        return info[0][1]
+        
+    def get_info(self):
+        return [str(self.id), self.word, self.lemma, self.pos_universal, self.pos_tag, self.detail_tag,
+                str(self.head), self.dep_tag, self.blank, self.auto_score]
+
+    def get_conllU_line(self, separator="\t"):
+        info = self.get_info()
+        return separator.join(info)
+
+
+
+class CoNLL09_Token():
+    def __init__(self, raw_line, word_ix):
+        info = raw_line.split()
+        # print(info)
+        # # ['1', 'Frau', 'Frau', 'Frau', 'NN', 'NN', '_', 'nom|sg|fem', '5', '5', 'CJ', 'CJ', '_', '_', 'AM-DIS', '_']
+        self.info = info
+        self.id = info[0] # 1-based ID as in the CoNLL file
+        self.position = word_ix # 0-based position in sentence
+        self.word = info[1]
+        self.lemma = info[2]
+        self.pos_universal = "_" # _convert_to_universal(self.pos_tag, self.lemma)
+        self.pos_tag = info[4]
+        self.head = info[8]
+        self.dep_tag = info[10]
+        self.detail_tag = "_"
+        self.is_pred = True if info[12] == "Y" else False
+        if self.is_pred:
+            self.pred_sense = info[13].strip("[]")
+            self.pred_sense_id = str(self.position) + "##" + self.pred_sense
+        else:
+            self.pred_sense = None
+            self.pred_sense_id = ""
+        if len(info) > 14:
+            self.labels = info[14:]
+        else:
+            self.labels = []
+
+    def get_conllU_line(self, separator="\t"):
+        # We want: [ID, FORM, LEMMA, UPOS, XPOS, FEATS, HEAD, DEPREL, DEPS, MISC]
+        tok_id = str(self.id) #.split("_")[0]
+        conllUinfo = [tok_id, self.word, self.lemma, self.pos_universal, self.pos_tag, self.detail_tag, self.head, self.dep_tag, "_", "_"]
+        return separator.join(conllUinfo)
+
+    def get_conll09_line(self, delim="\t"):
+        # We want:
+        # 1 Frau Frau Frau NN NN _ nom|sg|fem 5 5 CJ CJ _ _ AM-DIS _
+        # 10	fall	fall	fall	VB	VB	_	_	8	8	VC	VC	Y	fall.01	_	_	_	_	_
+        is_pred_str = "Y" if self.is_pred else "_"
+        sense_str = self.pred_sense if self.is_pred else "_"
+        info = [self.id, self.word, self.lemma, self.lemma, self.pos_tag, self.pos_tag, "_", self.detail_tag,
+                self.head, self.head, self.dep_tag, self.dep_tag, is_pred_str, sense_str] + self.labels
+        return delim.join(info)
+
+
+
+################################# GETTING SENTENCE ANNOTATIONS ####################################
+class AnnotatedSentence():
+    def __init__(self):
+        self.metadata = []
+        self.tokens = []
+
+    def get_words(self):
+        return [tok.word for tok in self.tokens]
+
+    def get_sentence(self):
+        return " ".join([tok.word for tok in self.tokens])
+
+    def get_pos_tags(self, universal=False):
+        if universal:
+            return [tok.pos_universal for tok in self.tokens]
+        else:
+            return [tok.pos_tag for tok in self.tokens]
+
+
+def get_annotation(raw_lines, raw_meta, token_class):
+    ann = AnnotatedSentence()
+    ann.metadata = [m.strip("\n") for m in raw_meta]
+    # Annotate the predicates and senses
+    real_index = 0
+    for i, line in enumerate(raw_lines):
+        tok = token_class(line, real_index)
+        ann.tokens.append(tok)
+        real_index += 1
+    return ann
+
+
+def read_conll(line_generator, chunk_size, token_class=CoNLLUP_Token, comment_str="###C:"):
+    n_sents = 0
+    annotated_sentences, buffer_meta, buffer_lst = [], [], []
+    for i, line in enumerate(line_generator):
+        if line.startswith(comment_str):
+            buffer_meta.append(line) 
+            continue
+        if len(line.split()) > 0:
+            buffer_lst.append(line)
+        else:
+            ann = get_annotation(buffer_lst, buffer_meta, token_class)
+            n_sents += 1
+            buffer_lst, buffer_meta = [], []
+            annotated_sentences.append(ann)
+        if chunk_size > 0 and n_sents == chunk_size: break
+    # logger.info("Read {} Sentences!".format(n_sents))
+    return annotated_sentences, n_sents
+
+    
+def read_conll_generator(filepath, token_class=CoNLLUP_Token, sent_sep=None, comment_str="###C:"):
+    buffer_meta, buffer_lst = [], []
+    sentence_finished = False
+    with open(filepath) as f:
+        for i, line in enumerate(f.readlines()):
+            if sent_sep and sent_sep in line: sentence_finished = True
+            if line.startswith(comment_str):
+                continue
+            if len(line.split()) > 0 and not sentence_finished:
+                buffer_lst.append(line)
+            else:
+                ann = get_annotation(buffer_lst, buffer_meta, token_class)
+                buffer_lst, buffer_meta = [], []
+                sentence_finished = False
+                yield ann
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