diff --git a/EP/__pycache__/cora.cpython-35.pyc b/EP/__pycache__/cora.cpython-35.pyc
deleted file mode 100644
index 9d7c440bca7e0dcdef453e3120e6ac9548292dea..0000000000000000000000000000000000000000
Binary files a/EP/__pycache__/cora.cpython-35.pyc and /dev/null differ
diff --git a/EP/__pycache__/initialize.cpython-35.pyc b/EP/__pycache__/initialize.cpython-35.pyc
deleted file mode 100644
index 301db6277e7cbd18b55079cc909d69a2eaa47d4a..0000000000000000000000000000000000000000
Binary files a/EP/__pycache__/initialize.cpython-35.pyc and /dev/null differ
diff --git a/EP/__pycache__/random_nodes_for_node_classification.cpython-35.pyc b/EP/__pycache__/random_nodes_for_node_classification.cpython-35.pyc
deleted file mode 100644
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diff --git a/Senseval_Prep/Senseval2/d00.pkl b/Senseval_Prep/Senseval2/d00.pkl
index 201e6830f541614bf0f729d4b5ef64d0ddbcb950..35ece51f061764d31abe7d63ab610ae11819ca8a 100644
Binary files a/Senseval_Prep/Senseval2/d00.pkl and b/Senseval_Prep/Senseval2/d00.pkl differ
diff --git a/Senseval_Prep/Senseval2/d01.pkl b/Senseval_Prep/Senseval2/d01.pkl
index 115c2c77b1715a39e161a3b71ec65bd93ed418e5..e91d5f897a4f1937b895fb736134c29397bd86b1 100644
Binary files a/Senseval_Prep/Senseval2/d01.pkl and b/Senseval_Prep/Senseval2/d01.pkl differ
diff --git a/Senseval_Prep/Senseval2/d02.pkl b/Senseval_Prep/Senseval2/d02.pkl
index 05bf45b5d04547c684b281b61446b2b11bee8501..1a7a40f14266c71b5d8f058c7c3c21c27779642a 100644
Binary files a/Senseval_Prep/Senseval2/d02.pkl and b/Senseval_Prep/Senseval2/d02.pkl differ
diff --git a/Senseval_Prep/senseval_preprocessing.py b/Senseval_Prep/senseval_preprocessing.py
index 6ef096d479843831debe5af6e478f36cab245107..8a0a5670e36fbd922b4bfd3f81f4908e241468ef 100644
--- a/Senseval_Prep/senseval_preprocessing.py
+++ b/Senseval_Prep/senseval_preprocessing.py
@@ -3,25 +3,26 @@ import pickle as pkl
from nltk.stem import WordNetLemmatizer
wnl = WordNetLemmatizer()
-file_path = "eng-all-words_seneval2.test.xml"
-#file_path = "english-all-words.xml"
+file_path2 = "eng-all-words_seneval2.test.xml" #senseval2
+file_path3 = "english-all-words.xml" #senseval3
-tree_paths3 = {"d000": "cl23.mrg", "d001": "wsj_1695.mrg", "d002":"wsj_1778.mrg"}
-tree_paths2 = {"d00": "wsj_0089.mrg", "d01": "wsj_0465.mrg", "d02": "wsj_1286.mrg"}
+tree_paths2 = {"d00": "wsj_0089.mrg", "d01": "wsj_0465.mrg", "d02": "wsj_1286.mrg"} #senseval2
+tree_paths3 = {"d000": "cl23.mrg", "d001": "wsj_1695.mrg", "d002":"wsj_1778.mrg"} #senseval3
-def get_stopword_list(path):
- with open (path, "r") as f:
+def get_stopword_list(stop_path):
+ with open (stop_path, "r") as f:
stopli = []
for line in f:
stopli.append(line[:-1])
return stopli
-def get_infos(path = tree_paths2["d00"]):
- with open (path, "r") as f:
+def get_infos(tree_path):
+ with open (tree_path, "r") as f:
file = f.read()
li = re.findall("\([\.,'`A-Z:]+\$? [&%:\\\/`'a-zA-Z0-9\.,\?!-]+\)", file)
return li
-def get_xml():
+
+def get_xml(file_path):
with open(file_path, "r") as f:
list_lines = f.readlines()[4:]
text_dict = {}
@@ -101,9 +102,9 @@ def validation_line(line):
line_info.append(line)
return line_info
-def get_sentence(key = "d000"):
+def get_sentence(key, file_path):
info_li = []
- for token in get_xml()[key]:
+ for token in get_xml(file_path)[key]:
if len(token)==1:
info_li.append(None)
elif len(token) == 0:
@@ -112,7 +113,7 @@ def get_sentence(key = "d000"):
info_li.append([token[1], token[2]])
return info_li
-def get_tag(treebank_tag):
+def get_wn_tag(treebank_tag):
if treebank_tag.startswith('J') or treebank_tag == "ADJ":
return "a"
elif treebank_tag.startswith('V'):
@@ -124,48 +125,65 @@ def get_tag(treebank_tag):
else:
return ''
-def get_tag_infos(path = tree_paths2["d00"]):
- infos = get_infos(path)
+def get_final_tag(treebank_tag):
+ if treebank_tag.startswith("NNP"):
+ return "PROPN"
+ elif treebank_tag.startswith('J') or treebank_tag == "ADJ":
+ return "ADJ"
+ elif treebank_tag.startswith('V') or treebank_tag == "MD":
+ return "VERB"
+ elif treebank_tag.startswith('N') or treebank_tag.startswith("PRO"):
+ return "NOUN"
+ elif treebank_tag.startswith('RB') or treebank_tag == "ADV":
+ return "ADV"
+ elif treebank_tag.startswith("CD"):
+ return "NUM"
+ else:
+ return ''
+
+def get_tag_infos(tree_path):
+ infos = get_infos(tree_path)
new_list = []
for elm in infos:
a = elm[1:-1].split()
- tag = get_tag(a[0])
+ tag = get_wn_tag(a[0])
+ gloss_tag = get_final_tag(a[0])
token = a[1]
if token == "'s":
token = "is"
if tag == "":
- new_list.append([str(wnl.lemmatize(token)).lower(), a[0], tag])
+ new_list.append([str(wnl.lemmatize(token)).lower(), a[0], tag, gloss_tag])
else:
- new_list.append([wnl.lemmatize(token, pos=tag), a[0], tag])
+ new_list.append([wnl.lemmatize(token, pos=tag).lower(), a[0], tag, gloss_tag])
return new_list
-def get_tag_and_info_list(key = "d00"):
- token_list = get_tag_infos(tree_paths2[key])
- info_list = get_sentence(key)
+def get_tag_and_info_list(key, file_path, tree_path):
+ token_list = get_tag_infos(tree_path[key])
+ info_list = get_sentence(key, file_path)
return token_list, info_list
-def delete_stopwords(key, path):
- stopwords = get_stopword_list(path)
- tokens, infos = get_tag_and_info_list(key)
- """
- print (len(tokens))
- print (len(get_infos(path)))
- print (len(infos))
- for idx in range(len(infos)):
- print (infos[idx])
- try:
- print (tokens[idx])
- print (get_infos(path)[idx])
- except IndexError:
- print ("foo")
- print ("\n")
- """
+def get_gloss_lemmas(path):
+ with open (path, "r") as f:
+ gloss_lemma_set = set()
+ for line in f.readlines():
+ gloss_lemma_set.add(line.split()[1])
+ return gloss_lemma_set
+
+def delete_stopwords(stop_path, key, gloss_path, file_path, tree_path):
+ stopwords = get_stopword_list(stop_path)
+ tokens, infos = get_tag_and_info_list(key, file_path, tree_path)
new_tokens = []
new_infos = []
+ gloss = get_gloss_lemmas(gloss_path)
+ punct = [",", ".", "!", "?", ":"]
for idx in range(len(infos)):
if infos[idx] == None:
if tokens[idx][0] in stopwords:
continue
+ elif tokens[idx][0] not in gloss:
+ continue
+ elif tokens[idx][0] in punct:
+ continue
else:
new_tokens.append(tokens[idx])
new_infos.append(infos[idx])
@@ -174,7 +192,6 @@ def delete_stopwords(key, path):
new_infos.append(infos[idx])
return new_tokens, new_infos
-
def get_sats(tokens, info):
sat_dict = {}
for elm in info:
@@ -209,23 +226,23 @@ def get_sats(tokens, info):
else:
new_tokens.append(tokens[idx])
new_info.append(info[idx])
- print (len(info), len(new_info))
- print (len(tokens), len(new_tokens))
return [new_tokens, new_info]
-def write_pkl(path="stopwords.txt"):
- for key in get_xml().keys():
- without_stop_tokens, without_stop_info = delete_stopwords(key,path)
-
+def write_pkl(version = 2, stop_path="stopwords.txt", gloss_path = "gloss_mapping.txt"):
+ file_path = ""
+ tree_path = ""
+ if version == 2:
+ file_path = file_path2
+ tree_path = tree_paths2
+ elif version == 3:
+ file_path = file_path3
+ tree_path = tree_paths3
+ for key in get_xml(file_path).keys():
+ without_stop_tokens, without_stop_info = delete_stopwords(stop_path, key, gloss_path, file_path, tree_path)
output = get_sats(without_stop_tokens, without_stop_info)
-
with open(key+".pkl", "wb") as f:
pkl.dump(output, f)
print (key, "Done")
-#write_pkl()
-
-def read_pkl(path = "d000.pkl"):
- with open (path, "rb") as f:
- li = pkl.load(f)
- return li
+if __name__ == "__main__":
+ write_pkl(version=3)
diff --git a/WSD/computed_keys.txt b/WSD/computed_keys.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b5ae4471a34f0516e0673a878b1f2f63e87220c5
--- /dev/null
+++ b/WSD/computed_keys.txt
@@ -0,0 +1,2081 @@
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+d002 d002.s081.t010 mayonnaise%1:13:00::
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+d002 d002.s100.t000 cupboard%1:06:00::
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+d002 d002.s100.t003 fly%2:35:00::
+d002 d002.s100.t006 trash_can%1:06:00::
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+d002 d002.s100.t011 walk%2:33:00::
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+d002 d002.s100.t014
+d002 d002.s100.t017 dog%1:18:02::
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+d002 d002.s100.t027 dog%1:18:02::
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+d002 d002.s100.t039 outside%3:00:04::
+d002 d002.s100.t040 trash%1:27:00::
+d002 d002.s100.t041 can%1:06:02::
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+d002 d002.s100.t045 concrete%1:27:00::
+d002 d002.s101.t002 realize%2:31:01::
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+d002 d002.s101.t018 house%1:14:01::
+d002 d002.s101.t021 wait%2:31:00::
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+d002 d002.s101.t027 come%2:42:03::
+d002 d002.s101.t028 home%1:15:03::
+d002 d002.s101.t030 shiver%2:29:00::
+d002 d002.s101.t034 be%2:42:01::
+d002 d002.s101.t040 get%2:39:13::
+d002 d002.s102.t003 life%1:09:00::
+d002 d002.s102.t006 be%2:42:01::
+d002 d002.s102.t008 frightened%5:00:00:afraid:00
+d002 d002.s103.t002 saw%2:35:00::
+d002 d002.s103.t004 picture%1:26:00::
+d002 d002.s103.t014 begin%2:41:04::
+d002 d002.s103.t017 cry%2:32:07::
+d002 d002.s106.t005 be%2:42:09::
+d002 d002.s106.t011
+d002 d002.s106.t014 evening%1:28:00::
+d002 d002.s106.t016 lot%1:23:00::
+d002 d002.s106.t018 people%1:14:01::
+d002 d002.s106.t020 dog%1:18:01::
+d002 d002.s106.t021 walk_around%2:41:00::
+d002 d002.s106.t024 drink%2:34:02::
+d002 d002.s106.t025 beer%1:13:00::
+d002 d002.s109.t001 be%2:42:01::
+d002 d002.s109.t003 sit_down%2:35:00::
+d002 d002.s109.t007 meet%2:42:00::
+d002 d002.s109.t010 new%3:00:00::
+d002 d002.s109.t011 therapy%1:04:00::
+d002 d002.s109.t012 client%1:18:00::
+d002 d002.s109.t015 couple%1:14:00::
+d002 d002.s109.t019 building%1:14:00::
+d002 d002.s109.t020 start%2:30:00::
+d002 d002.s109.t022 shake%2:38:02::
+d002 d002.s109.t024 like_crazy%4:02:00::
+d002 d002.s110.t001 be%2:42:07::
+d002 d002.s110.t003 flimsy%5:00:01:weak:00
+d002 d002.s110.t004 structure%1:07:00::
+d002 d002.s110.t006 build%2:30:10::
+d002 d002.s110.t010 support%1:10:01::
+d002 d002.s110.t016
+d002 d002.s111.t004 stop%2:41:00::
+d002 d002.s111.t006 breathe%2:32:00::
+d002 d002.s111.t009 moment%1:19:00::
+d002 d002.s111.t015 keep%2:42:00::
+d002 d002.s111.t018 come%2:42:05::
+d002 d002.s111.t021 lunge%2:38:00::
+d002 d002.s111.t024 doorway%1:06:00::
+d002 d002.s112.t001 needless%5:00:00:unnecessary:00
+d002 d002.s112.t004 say%2:32:04::
+d002 d002.s112.t007 be%2:42:13::
+d002 d002.s112.t009 interesting%3:00:00::
+d002 d002.s112.t010 first%5:00:00:best:00
+d002 d002.s112.t011 session%1:14:00::
+d002 d002.s115.t001 escape%2:30:04::
+d002 d002.s115.t004 unscathed%5:00:00:uninjured:00
+d002 d002.s116.t001 trouble%1:12:03::
+d002 d002.s116.t002 be%2:40:00::
+d002 d002.s116.t003 scar%2:35:00::
+d002 d002.s116.t004 family%1:14:04::
+d002 d002.s116.t009 get_through%2:38:00::
+d002 d002.s116.t011 phone_line%1:06:00::
+d002 d002.s116.t016 spend%2:42:00::
+d002 d002.s116.t019 horrible%5:00:00:alarming:00
+d002 d002.s116.t020 hour%1:07:00::
+d002 d002.s116.t023 know%2:31:11::
+d002 d002.s119.t003 be%2:42:07::
+d002 d002.s119.t006
+d002 d002.s119.t010 lawn%1:15:00::
+d002 d002.s119.t011 start%2:38:02::
+d002 d002.s119.t013 roll%2:35:01::
+d002 d002.s119.t015 ocean%1:23:00::
+d002 d002.s119.t016 wave%1:25:00::
+d002 d002.s120.t001 run%2:35:01::
+d002 d002.s120.t004 house%1:06:00::
+d002 d002.s120.t007 get%2:32:08::
+d002 d002.s120.t012 next%5:00:00:incoming:00
+d002 d002.s120.t013 tremor%1:26:00::
+d002 d002.s120.t014 throw%2:38:03::
+d002 d002.s120.t018 air%1:15:00::
+d002 d002.s120.t020 bounce%2:35:03::
+d002 d002.s120.t024 try%2:34:00::
+d002 d002.s120.t027 get%2:32:08::
+d002 d002.s120.t030
+d002 d002.s121.t001 be%2:42:00::
+d002 d002.s121.t003 fine%5:00:00:satisfactory:00
+d002 d002.s121.t010 freak%2:37:00::
+d002 d002.s122.t000 kitchen%1:06:00::
+d002 d002.s122.t001 full%3:00:01::
+d002 d002.s122.t004 crystal%1:06:02::
+d002 d002.s123.t000
+d002 d002.s123.t002 tape%1:06:04::
+d002 d002.s123.t006 room%1:26:00::
+d002 d002.s124.t002
+d002 d002.s124.t005 house%1:06:02::
+d002 d002.s124.t006 be%2:42:08::
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+d002 d002.s124.t019 be%2:41:00::
+d002 d002.s124.t020 fine%5:00:00:pure:02
+d002 d002.s125.t003 stand%2:31:00::
+d002 d002.s125.t006 lawn%1:15:00::
+d002 d002.s125.t011 wait%2:42:01::
+d002 d002.s125.t014 tremor%1:11:00::
+d002 d002.s125.t017 notice%2:32:01::
+d002 d002.s125.t021 earthworm%1:05:00::
+d002 d002.s125.t023 emerge%2:42:00::
+d002 d002.s125.t026 ground%1:17:01::
+d002 d002.s125.t028 slither%2:38:00::
+d002 d002.s125.t031 lawn%1:15:00::
+d002 d002.s128.t002 be%2:42:07::
+d002 d002.s128.t003 amazing%5:00:00:impressive:00
+d002 d002.s128.t006 second%1:23:00::
+d002 d002.s128.t010 change%2:30:02::
+d002 d002.s128.t012 life%1:09:00::
+d002 d002.s131.t001 guess%2:32:00::
+d002 d002.s131.t006 live%2:42:07::
+d002 d002.s131.t012 wait%2:31:00::
+d002 d002.s131.t018 aftershock%1:11:00::
+d002 d002.s132.t002 be%2:42:07::
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+d002 d002.s132.t006 accept%2:40:00::
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+d002 d002.s132.t015 second%1:23:00::
+d002 d002.s133.t001 wonder%2:32:12::
+d002 d002.s133.t005 be%2:42:02::
+d002 d002.s133.t006 able%5:00:00:capable:00
+d002 d002.s133.t009
+d002 d002.s136.t000 flesh%1:08:01::
+d002 d002.s136.t001 go%2:30:03::
+d002 d002.s136.t003 total%1:06:00::
+d002 d002.s136.t006 flight%1:04:01::
+d002 d002.s136.t008 fight%1:10:00::
+d002 d002.s137.t000 nausea%1:26:00::
+d002 d002.s137.t001 seem%2:42:00::
+d002 d002.s137.t003 commonplace%5:00:02:ordinary:00
+d002 d002.s137.t004 symptom%1:10:00::
+d002 d002.s138.t002 quiet%5:00:00:unostentatious:00
+d002 d002.s139.t001 walk%2:33:00::
+d002 d002.s139.t010 few%3:00:00::
+d002 d002.s139.t011 minute%1:10:00::
+d002 d002.s139.t015 morning%1:11:00::
+d002 d002.s140.t000 next%5:00:00:incoming:00
+d002 d002.s140.t005 homeless%5:00:00:unfortunate:00
+d002 d002.s140.t006 couple%1:17:00::
+d002 d002.s140.t009 bundle%2:29:00::
+d002 d002.s140.t013 blue%5:00:00:sexy:00
+d002 d002.s140.t014
+d002 d002.s140.t017 sit_up%2:29:00::
+d002 d002.s140.t020 say%2:42:00::
+d002 d002.s140.t023 good_morning%1:10:00::
+d002 d002.s140.t029 woman%1:18:02::
+d002 d002.s140.t030 smile%2:32:00::
+d002 d002.s140.t032 say%2:42:00::
+d002 d002.s140.t035
+d002 d002.s140.t039 great%5:00:00:pregnant:00
+d002 d002.s140.t043 be%2:42:01::
+d002 d002.s140.t044
+d002 d002.s141.t001 agree%2:40:02::
+d002 d002.s142.t001 be%2:42:07::
+d002 d002.s143.t000 great%5:00:01:extraordinary:00
diff --git a/WSD/wsd_method1.py b/WSD/wsd_method1.py
index 707d9c0bf1f51b2de6fc682a2971ed88bd884c69..8aa2c70bdfc0d9ba2c234835feef066aac536d4c 100644
--- a/WSD/wsd_method1.py
+++ b/WSD/wsd_method1.py
@@ -42,7 +42,8 @@ def open_mapping(filename):
def open_sense_keys(filename):
"""
-
+ open wn30-17 sense key mapping
+ returns a dictionary {(syn_id_30, pos):sense_key_17}
"""
with open(filename, 'r') as input:
sense_keys = {(line.split()[0], line.split()[3]):line.split()[2] for line in input.readlines()}
@@ -52,11 +53,10 @@ def map_words(sentence):
"""
takes a list of ambig words
mapps them to potential synsets
- returns a list of synset_id lists
+ returns a list of synset_id lists [ [[w1s1],[w1s2],[w1s3]] , [[w2s1],...] ,...]
"""
pos = ['n','v','a','r']
ambig_list = []
- #split = False
def get_lem_id(token):
if token in lemmata_mapping.keys():
ambig_list.append(lemmata_mapping[token][1])
@@ -76,20 +76,17 @@ def map_words(sentence):
for word in sentence:
add = False
- #print(word)
add = get_lem_id(word[0]+'/'+word[1])
- #print(add)
if add: continue
elif '-' in word[0]:
words = word[0].split('-')
for w in words:
add = get_node_id(w)
- #if add: split = True
else:
add = get_node_id(word[0])
if not add: ambig_list.append(['U'])
- #print(ambig_list)
+
return ambig_list
def embed(node_id):
@@ -97,23 +94,12 @@ def embed(node_id):
takes a node id (int)
returns it's embedding (array)
"""
- #l1 = pos_embeddings
- #l2 = lemmata_embeddings
- embedding = np.concatenate((id_embeddings[node_id],pos_embeddings[node_id],lex_file_embeddings[node_id],lemmata_embeddings[node_id]), axis=0)
+ labels = (id_embeddings[node_id],pos_embeddings[node_id],lex_file_embeddings[node_id],lemmata_embeddings[node_id])
+ embedding = np.concatenate(labels, axis=0)
return embedding
-#def concatenate(l1 , l2):
- """
- soll: konkatiniert die Embeddings ausgewählter Labels pro Knoten
- --> soll embed() werden
- ist: konkatiniert die Embeddings ausgewählter Labels aller Knoten
- """
- #embeddings = [np.concatenate((l1[i], l2[i]), axis=0) for i in range(len(l1))]
- #return embeddings
-
-
def get_distance(node_combi):
"""
takes a list of node embedding lists