diff --git a/systems/Run_Tree-RNN_Taggers.txt b/systems/Run_Tree-RNN_Taggers.txt
index 98a9dd2..fe8be10 100644
--- a/systems/Run_Tree-RNN_Taggers.txt
+++ b/systems/Run_Tree-RNN_Taggers.txt
@@ -14,4 +14,4 @@
 # RNN Tagger:
 time cmd/rnn-tagger-german-notokenize.sh /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu.tok > /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.RNNtagger.parsed.conll
 
-time cmd/rnn-tagger-german-notokenize.sh /home/daza/datasets/TIGER_conll/data_splits/test/Tiger.NewOrth.test.conll.tok > /home/daza/datasets/TIGER_conll/sys_outputs/Tiger.NewOrth.test.RNNTagger.conll
+time cmd/rnn-tagger-german-notokenize.sh /home/daza/datasets/TIGER_conll/data_splits/test/Tiger.NewOrth.test.conll.tok > /home/daza/datasets/TIGER_conll/sys_outputs/Tiger.NewOrth.test.RNNTagger.conll
\ No newline at end of file
diff --git a/systems/eval_old_vs_new_tiger.py b/systems/eval_old_vs_new_tiger.py
deleted file mode 100644
index 38dc597..0000000
--- a/systems/eval_old_vs_new_tiger.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import my_utils.file_utils as fu
-from lib.CoNLL_Annotation import read_conll, CoNLLUP_Token 
-from collections import Counter
-from germalemma import GermaLemma
-
-SPACY_NEW = "/home/daza/datasets/TIGER_conll/Tiger.NewOrth.train.spacy_parsed.conllu"
-CASES = "/home/daza/datasets/TIGER_conll/NewOrthProblems_Indices.train.txt"
-
-orth_dict = fu.file_to_dict("/vol/netapp/daza/datasets/TIGER_conll/TigerOrthMapping.train.json")
-new_to_old = {v:k for k,v in orth_dict.items()}
-
-
-if __name__ == "__main__":
-	line_generator = fu.file_generator(SPACY_NEW)
-	conll_sents, _ = read_conll(line_generator, chunk_size=60000, token_class=CoNLLUP_Token, comment_str="#")
-	special_cases = [int(line) for line in open(CASES).read().splitlines()]
-	checked_cases = []
-	
-	lemmatizer = GermaLemma()
-	
-	for ix, sent in enumerate(conll_sents):
-		if ix in special_cases:
-			for tok in sent.tokens:
-				old_word_change = new_to_old.get(tok.word)
-				if old_word_change:
-					try:
-						old_lemma = lemmatizer.find_lemma(old_word_change, tok.pos_tag)
-					except:
-						old_lemma = f"UNK_{tok.pos_tag}"
-					checked_cases.append((old_word_change, tok.word, old_lemma, tok.lemma))
-	
-	print(f"Cases checked: {len(checked_cases)}")
-	case_count = Counter(checked_cases).most_common()
-	fu.counter_to_file(case_count, "/home/daza/datasets/TIGER_conll/TigerLemmas_Old_New.tsv")
-	
\ No newline at end of file
diff --git a/systems/evaluate.py b/systems/evaluate.py
deleted file mode 100644
index 839cd37..0000000
--- a/systems/evaluate.py
+++ /dev/null
@@ -1,231 +0,0 @@
-from lib.CoNLL_Annotation import *
-from collections import Counter, defaultdict
-import pandas as pd
-import numpy as np
-from sklearn.metrics import precision_recall_fscore_support as eval_f1
-from tabulate import tabulate
-import logging, argparse, sys
-from datetime import datetime
-
-
-tree_tagger_fixes = {
-    "die": "der", 
-    "eine": "ein", 
-    "dass": "daß", 
-    "keine": "kein",
-    "dies": "dieser",
-    "erst": "erster",
-    "andere": "anderer",
-    "alle": "aller",
-    "Sie": "sie",
-    "wir": "uns", 
-    "alle": "aller",
-    "wenige": "wenig"
-}
-
-
-def save_evaluated(all_sys, all_gld, out_path, print_gold=True):
-    with open(out_path, "w") as out:
-        if print_gold:
-            out.write(f"ORIGINAL_CORPUS_TAGS\n\nTAG\tGLD_COUNT\tSYS_COUNT\n")
-            for g_tag,g_count in sorted(all_gld.items()):
-                s_count = all_sys.get(g_tag, 0)
-                out.write(f"{g_tag}\t{g_count}\t{s_count}\n")
-        
-        out.write("\n\nSYSTEM_ONLY_TAGS\n\nTAG\tG_COUNT\tSYS_COUNT\n")
-        for s_tag,s_count in sorted(all_sys.items()):
-            g_count = all_gld.get(s_tag, 0)
-            if g_count == 0:
-                out.write(f"{s_tag}\t{g_count}\t{s_count}\n")
-    
-
-
-def eval_lemma(sys, gld):
-    match, err, symbol = 0, 0, []
-    y_gld, y_pred, mistakes = [], [], []
-    for i, gld_tok in enumerate(gld.tokens):
-        sys_lemma = sys.tokens[i].lemma
-        # sys_lemma = tree_tagger_fixes.get(sys.tokens[i].lemma, sys.tokens[i].lemma)  # Omit TreeTagger "errors" because of article lemma disagreement 
-        y_gld.append(gld_tok.pos_tag)
-        y_pred.append(sys_lemma)
-        if gld_tok.lemma == sys_lemma:
-            match += 1
-        elif not sys.tokens[i].lemma.isalnum(): # Turku does not lemmatize symbols (it only copies them) => ERR ((',', '--', ','), 43642)
-            symbol.append(sys.tokens[i].lemma)
-            if sys.tokens[i].word == sys.tokens[i].lemma:
-                match += 1
-            else:
-                err += 1
-        else:
-            err += 1
-            mistakes.append((gld_tok.word, gld_tok.lemma, sys.tokens[i].lemma))
-    return y_gld, y_pred, match, err, symbol, mistakes
-    
-
-def eval_pos(sys, gld):
-    match, mistakes = 0, []
-    y_gld, y_pred = [], []
-    for i, gld_tok in enumerate(gld.tokens):
-        y_gld.append(gld_tok.pos_tag)
-        y_pred.append(sys.tokens[i].pos_tag)
-        # pos_all_pred[gld_tok.pos_tag] += 1
-        # pos_all_gold[sys.tokens[i].pos_tag] += 1
-        if gld_tok.pos_tag == sys.tokens[i].pos_tag:
-            match += 1
-        elif gld_tok.pos_tag == "$." and sys.tokens[i].pos_tag == "$":
-            match += 1
-            y_pred = y_pred[:-1] + ["$."]
-        else:
-            mistakes.append((gld_tok.word, gld_tok.pos_tag, sys.tokens[i].pos_tag))
-    return y_gld, y_pred, match, mistakes
-
-
-
-if __name__ == "__main__":
-    """
-        EVALUATIONS: 
-        
-        ********** TIGER CORPUS ALL ************
-        
-            python systems/evaluate.py -t Turku --corpus_name Tiger --gld_token_type CoNLL09_Token \
-                --sys_file /home/daza/datasets/TIGER_conll/tiger_turku_parsed.conllu \
-                --gld_file /home/daza/datasets/TIGER_conll/tiger_release_aug07.corrected.16012013.conll09
-                
-            python systems/evaluate.py -t SpaCy --corpus_name Tiger --gld_token_type CoNLL09_Token \
-                --sys_file /home/daza/datasets/TIGER_conll/tiger_spacy_parsed.conllu \
-                --gld_file /home/daza/datasets/TIGER_conll/tiger_release_aug07.corrected.16012013.conll09
-                
-            python systems/evaluate.py -t RNNTagger --corpus_name Tiger --gld_token_type CoNLL09_Token \
-                --sys_file /home/daza/datasets/TIGER_conll/tiger_all.parsed.RNNTagger.conll \
-                --gld_file /home/daza/datasets/TIGER_conll/tiger_release_aug07.corrected.16012013.conll09
-            
-            python systems/evaluate.py -t TreeTagger --corpus_name Tiger --gld_token_type CoNLL09_Token \
-                --sys_file /home/daza/datasets/TIGER_conll/tiger_all.parsed.TreeTagger.conll \
-                --gld_file /home/daza/datasets/TIGER_conll/tiger_release_aug07.corrected.16012013.conll09
-            
-        
-        ********** TIGER CORPUS TEST ************
-        
-        python systems/evaluate.py -t SpaCy --corpus_name TigerTestOld \
-        --sys_file /home/daza/datasets/TIGER_conll/tiger_spacy_parsed.test.conllu \
-        --gld_file /home/daza/datasets/TIGER_conll/data_splits/test/Tiger.OldOrth.test.conll
-        
-        python systems/evaluate.py -t SpaCy --corpus_name TigerTestNew \
-        --sys_file /home/daza/datasets/TIGER_conll/Tiger.NewOrth.test.spacy_parsed.conllu\
-        --gld_file /home/daza/datasets/TIGER_conll/data_splits/test/Tiger.NewOrth.test.conll
-        
-        
-        python systems/evaluate.py -t Turku --corpus_name TigerTestNew \
-        --sys_file /home/daza/datasets/TIGER_conll/sys_outputs/Tiger.NewOrth.test.turku_parsed.conllu \
-        --gld_file /home/daza/datasets/TIGER_conll/data_splits/test/Tiger.NewOrth.test.conll
-        
-        ********** UNIVERSAL DEPENDENCIES TEST-SET ************
-
-            python systems/evaluate.py -t Turku --corpus_name DE_GSD \
-            --sys_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu.parsed.0.conllu \
-            --gld_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu    
-            
-            python systems/evaluate.py -t SpaCyGL --corpus_name DE_GSD \
-                --sys_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.parsed.germalemma.conllu \
-                --gld_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu    
-            
-            python systems/evaluate.py -t SpaCy --corpus_name DE_GSD \
-                --sys_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.parsed.conllu \
-                --gld_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu 
-                
-            python systems/evaluate.py -t RNNTagger --corpus_name DE_GSD \
-                --sys_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.RNNtagger.parsed.conll \
-                --gld_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu
-            
-            python systems/evaluate.py -t TreeTagger --corpus_name DE_GSD \
-                --sys_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.treetagger.parsed.conll \
-                --gld_file /home/daza/datasets/ud-treebanks-v2.2/UD_German-GSD/de_gsd-ud-test.conllu
-                
-    """
-    
-    # =====================================================================================
-    #                    INPUT PARAMS 
-    # =====================================================================================
-    parser = argparse.ArgumentParser()
-    parser.add_argument("-s", "--sys_file", help="System output in CoNLL-U Format", required=True)
-    parser.add_argument("-g", "--gld_file", help="Gold Labels to evaluate in CoNLL-U Format", required=True)
-    parser.add_argument("-c", "--corpus_name", help="Corpus Name for Gold Labels", required=True)
-    parser.add_argument("-t", "--type_sys", help="Which system produced the outputs", default="system")
-    parser.add_argument("-gtt", "--gld_token_type", help="CoNLL Format of the Gold Data", default="CoNLLUP_Token")
-    parser.add_argument("-cs", "--comment_str", help="CoNLL Format of comentaries inside the file", default="#")
-    args = parser.parse_args()
-    
-    # =====================================================================================
-    #                    LOGGING INFO ...
-    # =====================================================================================
-    logger = logging.getLogger(__name__)
-    console_hdlr = logging.StreamHandler(sys.stdout)
-    file_hdlr = logging.FileHandler(filename=f"logs/Eval_{args.corpus_name}.{args.type_sys}.log")
-    logging.basicConfig(level=logging.INFO, handlers=[console_hdlr, file_hdlr])
-    now_is = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    logger.info(f"\n\nEvaluating {args.corpus_name} Corpus {now_is}")
-
-    # Read the Original GOLD Annotations [CoNLL09, CoNLLUP]
-    gld_generator = read_conll_generator(args.gld_file, token_class=get_token_type(args.gld_token_type), comment_str=args.comment_str)
-    # Read the Annotations Generated by the Automatic Parser [Turku, SpaCy, RNNTagger] 
-    if args.type_sys == "RNNTagger":
-        sys_generator = read_conll_generator(args.sys_file, token_class=RNNTagger_Token, comment_str="#")
-    elif args.type_sys == "TreeTagger":
-        sys_generator = read_conll_generator(args.sys_file, token_class=RNNTagger_Token, sent_sep="</S>", comment_str="#")
-    else:
-        sys_generator = read_conll_generator(args.sys_file, token_class=CoNLLUP_Token, comment_str="#")
-    
-    lemma_all_match, lemma_all_err, lemma_all_mistakes = 0, 0, []
-    lemma_all_symbols, sys_only_lemmas = [], []
-    pos_all_match, pos_all_err, pos_all_mistakes = 0, 0, []
-    pos_all_pred, pos_all_gld = [], []
-    lemma_all_pred, lemma_all_gld = [], []
-    n_sents = 0
-    
-    for i, (s,g) in enumerate(zip(sys_generator, gld_generator)):
-        # print([x.word for x in s.tokens])
-        # print([x.word for x in g.tokens])
-        assert len(s.tokens) == len(g.tokens), f"Token Mismatch! S={len(s.tokens)} G={len(g.tokens)} IX={i+1}"
-        n_sents += 1
-        # Lemmas ...
-        lemma_gld, lemma_pred, lemma_match, lemma_err, lemma_sym, mistakes = eval_lemma(s,g)
-        lemma_all_match += lemma_match
-        lemma_all_err += lemma_err
-        lemma_all_mistakes += mistakes
-        lemma_all_symbols += lemma_sym
-        lemma_all_pred += lemma_pred
-        lemma_all_gld += lemma_gld
-        # POS Tags ...
-        pos_gld, pos_pred, pos_match, pos_mistakes = eval_pos(s, g)
-        pos_all_pred += pos_pred 
-        pos_all_gld += pos_gld
-        pos_all_match +=  pos_match
-        pos_all_err += len(pos_mistakes)
-        pos_all_mistakes += pos_mistakes
-    
-    logger.info(f"A total of {n_sents} sentences were analyzed")
-    
-    # Lemmas ...
-    logger.info(f"Lemma Matches = {lemma_all_match} || Errors = {lemma_all_err} || Symbol Chars = {len(lemma_all_symbols)}")
-    logger.info(f"Lemma Accuracy = {(lemma_all_match*100/(lemma_all_match + lemma_all_err)):.2f}%\n")
-    lemma_miss_df = pd.DataFrame(lemma_all_mistakes, columns =['Gold_Word', 'Gold_Lemma', 'Sys_Lemma']).value_counts()
-    lemma_miss_df.to_csv(path_or_buf=f"outputs/LemmaErrors.{args.corpus_name}.{args.type_sys}.tsv", sep="\t")
-    save_evaluated(Counter(lemma_all_pred), Counter(lemma_all_gld), 
-                            f"outputs/Lemma-Catalogue.{args.corpus_name}.{args.type_sys}.txt", print_gold=False)
-    
-    # POS Tags ...
-    logger.info(f"POS Matches = {pos_all_match} || Errors = {pos_all_err}")
-    logger.info(f"POS Tagging Accuracy = {(pos_all_match*100/(pos_all_match + pos_all_err)):.2f}%\n")
-    pos_miss_df = pd.DataFrame(pos_all_mistakes, columns =['Gold_Word', 'Gold_POS', 'Sys_POS']).value_counts()
-    pos_miss_df.to_csv(path_or_buf=f"outputs/POS-Errors.{args.corpus_name}.{args.type_sys}.tsv", sep="\t")
-    save_evaluated(Counter(pos_all_pred), Counter(pos_all_gld), f"outputs/POS-Catalogue.{args.corpus_name}.{args.type_sys}.txt")
-    
-    ordered_labels = sorted(set(pos_all_gld))
-    p_labels, r_labels, f_labels, support = eval_f1(y_true=pos_all_gld, y_pred=pos_all_pred, labels=ordered_labels , average=None)
-    scores_per_label = zip(ordered_labels, [x*100 for x in p_labels], [x*100 for x in r_labels], [x*100 for x in f_labels])
-    logger.info("\n\n")
-    logger.info(tabulate(scores_per_label, headers=["POS Tag","Precision", "Recall", "F1"], floatfmt=".2f"))
-    p_labels, r_labels, f_labels, support = eval_f1(y_true=np.array(pos_all_gld), y_pred=np.array(pos_all_pred), average='macro', zero_division=0)
-    logger.info(f"Total Prec = {p_labels*100}\tRec = {r_labels*100}\tF1 = {f_labels*100}")
-    
-    
\ No newline at end of file
diff --git a/systems/parse_spacy.py b/systems/parse_spacy.py
index 3c56233..90ca237 100644
--- a/systems/parse_spacy.py
+++ b/systems/parse_spacy.py
@@ -29,9 +29,6 @@
 		conll_lines.append("\t".join(content))
 	return "\n".join(conll_lines)
 
-
-# def freeling_lemma_lookup():
-# 	dicts_path = "/home/daza/Frameworks/FreeLing/data/de/dictionary/entries/"
 	
 def find_germalemma(word, pos, spacy_lemma):
 	simplify_pos = {"ADJA":"ADJ", "ADJD":"ADJ",
@@ -81,7 +78,6 @@
 		time python systems/parse_spacy.py --corpus_name DeReKo_a00 --comment_str "#" \
 			-i /export/netapp/kupietz/N-GRAMM-STUDIE/conllu/a00.conllu.gz \
 			-o /export/netapp/kupietz/N-GRAMM-STUDIE/conllu/0_SpaCyParsed/a00.spacy.gl.conllu
-			
 	"""
 	
 	parser = argparse.ArgumentParser()
diff --git a/systems/parse_turku.py b/systems/parse_turku.py
index 284dbd4..668a48c 100644
--- a/systems/parse_turku.py
+++ b/systems/parse_turku.py
@@ -6,6 +6,7 @@
 import my_utils.file_utils as fu
 import argparse
 
+
 if __name__ == "__main__":
     
     """
@@ -21,6 +22,7 @@
     
     parser = argparse.ArgumentParser()
     parser.add_argument("-i", "--input_file", help="Input Corpus", required=True)
+    parser.add_argument("-o", "--output_file", help="Output Parsed Corpus", default=None)
     parser.add_argument("-n", "--corpus_name", help="Corpus Name", default="Corpus")
     parser.add_argument("-gtt", "--gld_token_type", help="CoNLL Format of the Gold Data", default="CoNLL09_Token")
     parser.add_argument("-c", "--comment_str", help="CoNLL Format of comentaries inside the file", default="#")
@@ -29,6 +31,8 @@
     file_has_next, chunk_ix = True, 0
     CHUNK_SIZE = 10000
     
+    output_file = args.input_file if not args.output_file else args.output_file
+    
     # =====================================================================================
     #                    LOGGING INFO ...
     # =====================================================================================
@@ -48,7 +52,7 @@
         raw_text, file_has_next, n_sents = fu.get_file_chunk(line_generator, chunk_size=CHUNK_SIZE, token_class=get_token_type(args.gld_token_type), comment_str=args.comment_str)
         total_processed_sents += n_sents
         if len(raw_text) > 0:
-            fu.turku_parse_file(raw_text, args.input_file, chunk_ix)
+            fu.turku_parse_file(raw_text, output_file, chunk_ix)
             now = time.time()
             elapsed = (now - start)
             logger.info(f"Time Elapsed: {elapsed}. Processed {total_processed_sents}. [{total_processed_sents/elapsed} Sents/sec]\n") # Toks/Sec???