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Alain Shakour
clowdflows
Commits
901c3e49
Commit
901c3e49
authored
Jun 05, 2015
by
hiphop
Browse files
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new widgets
parent
9b4e3001
Changes
11
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11 changed files
with
881 additions
and
23 deletions
+881
-23
workflows/nlp/library.py
workflows/nlp/library.py
+153
-14
workflows/nlp/package_data/widgets/09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2.json
...ge_data/widgets/09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2.json
+281
-0
workflows/nlp/package_data/widgets/1e75106f-ba4c-4b2b-a8cf-fb0f9c1d42f8.json
...ge_data/widgets/1e75106f-ba4c-4b2b-a8cf-fb0f9c1d42f8.json
+91
-0
workflows/nlp/package_data/widgets/27273666-764d-458d-9513-0715ba2e6b4d.json
...ge_data/widgets/27273666-764d-458d-9513-0715ba2e6b4d.json
+1
-1
workflows/nlp/package_data/widgets/4414ef0d-4dde-46ee-ba7b-12da93daef15.json
...ge_data/widgets/4414ef0d-4dde-46ee-ba7b-12da93daef15.json
+195
-0
workflows/nlp/package_data/widgets/4eec620e-f919-47d5-99f9-846ada308ac2.json
...ge_data/widgets/4eec620e-f919-47d5-99f9-846ada308ac2.json
+1
-1
workflows/nlp/package_data/widgets/5c7768f9-4449-469b-bae1-f56e9e48be34.json
...ge_data/widgets/5c7768f9-4449-469b-bae1-f56e9e48be34.json
+1
-1
workflows/nlp/package_data/widgets/87ad3c66-160a-48d9-b922-37bfc9f773d6.json
...ge_data/widgets/87ad3c66-160a-48d9-b922-37bfc9f773d6.json
+1
-1
workflows/nlp/package_data/widgets/8a8f2aee-dc2e-4e1e-85d5-c977dc5c2867.json
...ge_data/widgets/8a8f2aee-dc2e-4e1e-85d5-c977dc5c2867.json
+3
-3
workflows/nlp/package_data/widgets/c47d5621-c5c4-464a-b502-5623c0193b34.json
...ge_data/widgets/c47d5621-c5c4-464a-b502-5623c0193b34.json
+19
-2
workflows/nlp/package_data/widgets/f3e3b0c7-39e1-4e7e-ba94-514d13864823.json
...ge_data/widgets/f3e3b0c7-39e1-4e7e-ba94-514d13864823.json
+135
-0
No files found.
workflows/nlp/library.py
View file @
901c3e49
...
...
@@ -8,9 +8,6 @@ import json
import
re
import
itertools
webservices_url
=
"http://vihar.ijs.si:8104"
def
merge_sentences
(
input_dict
):
"""
Merges the input sentences in XML according to the specified method.
...
...
@@ -57,27 +54,33 @@ def load_corpus2(input_dict):
'''
Parses an input file and encodes it in base 64.
'''
use_text
=
input_dict
[
"use_text"
]
==
"true"
if
input_dict
[
u
"text"
]
==
""
:
if
use_text
:
fname
=
"input_string.txt"
text
=
input_dict
[
u
"text"
].
strip
()
if
len
(
text
)
==
0
:
raise
Exception
(
"Please input text or uncheck the Use text checkbox."
)
data
=
base64
.
b64encode
(
text
)
else
:
f
=
safeOpen
(
input_dict
[
'file'
])
fname
=
os
.
path
.
basename
(
input_dict
[
'file'
])
data
=
base64
.
b64encode
(
f
.
read
())
else
:
fname
=
"input_string.txt"
data
=
base64
.
b64encode
(
input_dict
[
u
"text"
].
strip
())
#define web service
webservices_url
=
"http://vihar.ijs.si:8104"
webservice_url
=
webservices_url
+
"/parseFile"
params
=
{
"filename"
:
fname
,
"text"
:
data
}
#set params
#call web service
resp
=
post
(
webservice_url
,
params
=
params
)
content
=
json
.
loads
(
resp
.
content
)[
u
'parseFileResponse'
][
u
'parseFileResult'
]
"""
if content[u"error"] != "":
raise Exception(content[u"error"])
else:
return
{
'corpus'
:
content
[
u
"resp"
]}
"""
return
{
'corpus'
:
content
[
u
"resp"
]}
def
load_tagged_corpus
(
input_dict
):
"""
...
...
@@ -90,6 +93,7 @@ def load_tagged_corpus(input_dict):
return
{
'annotations'
:
data
}
def
totrtale_request
(
params
):
webservices_url
=
"http://vihar.ijs.si:8104"
webservice_url
=
webservices_url
+
"/runToTrTaLe"
return
post
(
webservice_url
,
params
=
params
)
...
...
@@ -163,7 +167,7 @@ def nlp_totrtale2(input_dict, widget):
sub_params
[
"text"
]
=
predhead
+
title
+
head
+
document_text
[
prev_j
:
curr_j
+
2
]
+
tail
else
:
sub_params
[
"text"
]
=
predhead
+
head
+
document_text
[
prev_j
:
curr_j
+
2
]
+
tail
results
.
append
(
pool
.
apply_async
(
totrtale_request
,
args
=
[
sub_params
]))
if
prev_j
==
0
:
single_docs
.
append
(
0
)
...
...
@@ -188,7 +192,6 @@ def nlp_totrtale2(input_dict, widget):
documents_size
+=
doc_len
if
documents_size
>
DOCUMENTS_SIZE
or
(
document_num
)
%
10
==
0
or
i
==
len
(
documents
)
-
1
:
#print "Log:",process_num, "process added to queue with", document_num, "documents"
documents_size
=
0
document_num
=
0
sub_params
=
copy
.
deepcopy
(
params
)
...
...
@@ -200,6 +203,8 @@ def nlp_totrtale2(input_dict, widget):
single_docs
.
append
(
-
1
)
pool
.
close
()
response
=
[
""
for
i
in
results
]
progress
=
[
True
]
...
...
@@ -237,8 +242,6 @@ def nlp_totrtale2(input_dict, widget):
response
[
i
]
=
resp
[
"resp"
]
else
:
if
single_docs
[
i
]
in
[
0
,
1
]:
#print "remove back", i, single_docs[i]
#pos1 = resp["resp"].find("<p>")
pos2
=
resp
[
"resp"
].
find
(
"</TEXT>"
)
response
[
i
]
=
resp
[
"resp"
][:
pos2
]
else
:
...
...
@@ -302,6 +305,70 @@ def nlp_term_extraction(input_dict):
threshold
=
0
)
return
{
'candidates'
:
response
[
'candidates'
]}
def
get_default_stop_word_list
(
lang
):
if
lang
==
"en"
:
return
[
"et al"
]
elif
lang
==
"sl"
:
return
[
"itd"
,
"slon"
,
"ovira"
,
"zob"
]
def
nlp_term_extraction2
(
input_dict
):
'''
Term extraction from totrtale annotations.
'''
ws_url
=
"http://vihar.ijs.si:8081/call"
annotations
=
input_dict
[
'annotations'
]
lang
=
input_dict
[
'lang'
]
stop_list_checkbox
=
input_dict
[
"stop_list"
]
==
"true"
user_stop_words
=
[]
if
input_dict
[
'stop_words_file'
]
!=
""
:
user_stop_words
=
safeOpen
(
input_dict
[
'stop_words_file'
]).
read
()
try
:
user_stop_words
.
decode
(
"utf-8"
)
except
Exception
:
raise
Exception
(
"Please make sure that your stop words list is encoded in UTF-8."
)
user_stop_words
=
user_stop_words
.
split
(
"
\n
"
)
if
'<TEI xmlns="http://www.tei-c.org/ns/1.0">'
in
annotations
:
annotations
=
TEItoTab
(
annotations
)
if
lang
==
"sl"
:
reference_corpus
=
input_dict
[
"slovene_reference_corpus"
]
elif
lang
==
"en"
:
reference_corpus
=
input_dict
[
"english_reference_corpus"
]
params
=
{
"corpus"
:
annotations
,
"lang"
:
lang
,
"reference_corpus"
:
reference_corpus
}
response
=
post
(
ws_url
,
params
=
params
)
resp
=
json
.
loads
(
response
.
content
)[
u
'callResponse'
][
u
'callResult'
]
stop_list
=
[]
if
stop_list_checkbox
:
stop_list
=
get_default_stop_word_list
(
lang
)
stop_list
=
set
(
stop_list
+
user_stop_words
)
if
len
(
stop_list
)
>
0
:
resp
=
resp
.
split
(
"
\n
"
)
i
=
0
while
i
<
len
(
resp
):
increase
=
True
line
=
resp
[
i
]
if
len
(
line
)
>
0
:
term
=
line
.
split
(
"
\t
"
)[
1
][
1
:
-
1
]
for
word
in
term
.
split
(
" "
):
if
word
.
lower
()
in
stop_list
:
increase
=
False
resp
.
pop
(
i
)
break
if
increase
:
i
+=
1
resp
=
"
\n
"
.
join
(
resp
)
return
{
'candidates'
:
resp
}
def
nlp_def_extraction_patterns
(
input_dict
):
'''
...
...
@@ -320,6 +387,26 @@ def nlp_def_extraction_patterns(input_dict):
lang
=
lang
,
pattern
=
pattern
)
return
{
'sentences'
:
response
[
'candidates'
]}
def
nlp_def_extraction_patterns2
(
input_dict
):
'''
Definition extraction using pre-defined patterns.
'''
annotations
=
input_dict
[
'annotations'
]
lang
=
input_dict
[
'lang'
]
pattern
=
input_dict
[
'pattern'
]
if
'<TEI xmlns="http://www.tei-c.org/ns/1.0">'
in
annotations
:
annotations
=
TEItoTab
(
annotations
)
ws_url
=
"http://vihar.ijs.si:8081/patDefSent"
params
=
{
"corpus"
:
annotations
,
"pattern"
:
pattern
,
"lang"
:
lang
}
response
=
post
(
ws_url
,
params
=
params
)
response
=
json
.
loads
(
response
.
content
)[
u
'patDefSentResponse'
][
u
'patDefSentResult'
]
return
{
'sentences'
:
response
}
def
nlp_def_extraction_terms
(
input_dict
):
'''
...
...
@@ -348,6 +435,40 @@ def nlp_def_extraction_terms(input_dict):
num_multiterms
=
num_multiterms
,
term_beginning
=
term_beginning
)
return
{
'sentences'
:
response
[
'candidates'
]}
def
nlp_def_extraction_terms2
(
input_dict
):
'''
Definition extraction using terms.
'''
annotations
=
input_dict
[
'annotations'
]
term_candidates
=
input_dict
[
'term_candidates'
]
lang
=
input_dict
[
'lang'
]
terms_per_sentence
=
input_dict
[
'terms_per_sentence'
]
nominatives
=
input_dict
[
'nominatives'
]
threshold
=
input_dict
[
'threshold'
]
verb_two_terms
=
input_dict
[
'verb_two_terms'
]
multiword_term
=
input_dict
[
'multiword_term'
]
num_multiterms
=
input_dict
[
'num_multiterms'
]
term_beginning
=
input_dict
[
'term_beginning'
]
if
'<TEI xmlns="http://www.tei-c.org/ns/1.0">'
in
annotations
:
annotations
=
TEItoTab
(
annotations
)
ws_url
=
"http://vihar.ijs.si:8081/termDefSent"
params
=
{
"corpus"
:
annotations
,
"candidates"
:
term_candidates
,
"lang"
:
lang
,
"nominatives"
:
nominatives
,
"terms_per_sentence"
:
terms_per_sentence
,
"select"
:
threshold
,
"verb_two_terms"
:
verb_two_terms
,
"multiword_term"
:
multiword_term
,
"num_multiterms"
:
num_multiterms
,
"term_beginning"
:
term_beginning
}
response
=
post
(
ws_url
,
params
=
params
)
response
=
json
.
loads
(
response
.
content
)[
u
'termDefSentResponse'
][
u
'termDefSentResult'
]
return
{
'sentences'
:
response
}
def
nlp_def_extraction_wnet
(
input_dict
):
'''
...
...
@@ -364,6 +485,22 @@ def nlp_def_extraction_wnet(input_dict):
response
=
ws
.
client
.
GlossaryExtractionByWnet
(
corpus
=
annotations
,
lang
=
lang
)
return
{
'sentences'
:
response
[
'candidates'
]}
def
nlp_def_extraction_wnet2
(
input_dict
):
'''
Definition extraction using WordNet.
'''
annotations
=
input_dict
[
'annotations'
]
lang
=
input_dict
[
'lang'
]
if
'<TEI xmlns="http://www.tei-c.org/ns/1.0">'
in
annotations
:
annotations
=
TEItoTab
(
annotations
)
ws_url
=
"http://vihar.ijs.si:8081/wnetDefSent"
params
=
{
"corpus"
:
annotations
,
"lang"
:
lang
}
response
=
post
(
ws_url
,
params
=
params
)
response
=
json
.
loads
(
response
.
content
)[
u
'wnetDefSentResponse'
][
u
'wnetDefSentResult'
]
return
{
'sentences'
:
response
}
def
TEItoTab
(
text
):
mask1
=
[
"
\t
TOK
\t
"
,
"
\t
"
,
"
\t\n
"
]
...
...
@@ -400,4 +537,6 @@ def TEItoTab(text):
newText
.
append
(
"<TEXT title="
+
title
+
">
\t\n
"
)
elif
"</body>"
in
l
:
newText
.
append
(
"</TEXT>
\t\n
"
)
return
""
.
join
(
newText
)
\ No newline at end of file
return
""
.
join
(
newText
)
\ No newline at end of file
workflows/nlp/package_data/widgets/09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2.json
0 → 100644
View file @
901c3e49
[
{
"model"
:
"workflows.abstractwidget"
,
"fields"
:
{
"category"
:
"9a30eafc-37b8-48f2-8a92-692c4b324dff"
,
"treeview_image"
:
""
,
"uid"
:
"09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2"
,
"is_streaming"
:
false
,
"package"
:
"nlp"
,
"interaction_view"
:
""
,
"has_progress_bar"
:
false
,
"image"
:
""
,
"description"
:
""
,
"static_image"
:
"nlp.png"
,
"action"
:
"nlp_def_extraction_terms2"
,
"visualization_view"
:
""
,
"streaming_visualization_view"
:
""
,
"post_interact_action"
:
""
,
"wsdl_method"
:
""
,
"wsdl"
:
""
,
"interactive"
:
false
,
"windows_queue"
:
false
,
"order"
:
1
,
"name"
:
"Definition extraction by terms2"
}
},
{
"model"
:
"workflows.abstractinput"
,
"fields"
:
{
"widget"
:
"09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2"
,
"name"
:
"First term should be a multi-word term"
,
"short_name"
:
"mwt"
,
"default"
:
"false"
,
"description"
:
"First term should be a multi-word term"
,
"required"
:
false
,
"multi"
:
false
,
"parameter_type"
:
"checkbox"
,
"variable"
:
"multiword_term"
,
"parameter"
:
true
,
"order"
:
7
,
"uid"
:
"25c57fa3-b085-4edf-a0ce-674f1dcd90f2"
}
},
{
"model"
:
"workflows.abstractinput"
,
"fields"
:
{
"widget"
:
"09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2"
,
"name"
:
"Annotations"
,
"short_name"
:
"ann"
,
"default"
:
""
,
"description"
:
"Totrtale annotations"
,
"required"
:
true
,
"multi"
:
false
,
"parameter_type"
:
null
,
"variable"
:
"annotations"
,
"parameter"
:
false
,
"order"
:
10
,
"uid"
:
"2ff7416f-417f-4033-ac66-5e9a386d1a5a"
}
},
{
"model"
:
"workflows.abstractinput"
,
"fields"
:
{
"widget"
:
"09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2"
,
"name"
:
"Threshold top % terms"
,
"short_name"
:
"thr"
,
"default"
:
"2%"
,
"description"
:
"Threshold"
,
"required"
:
true
,
"multi"
:
false
,
"parameter_type"
:
"text"
,
"variable"
:
"threshold"
,
"parameter"
:
true
,
"order"
:
5
,
"uid"
:
"929e4938-f51d-45cd-b8f1-0cbe6ea0d790"
}
},
{
"model"
:
"workflows.abstractinput"
,
"fields"
:
{
"widget"
:
"09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2"
,
"name"
:
"Multi-terms in a sentence"
,
"short_name"
:
"mtn"
,
"default"
:
"1"
,
"description"
:
"Multi-terms in a sentence"
,
"required"
:
false
,
"multi"
:
false
,
"parameter_type"
:
"text"
,
"variable"
:
"num_multiterms"
,
"parameter"
:
true
,
"order"
:
8
,
"uid"
:
"a49780d2-43cf-4bcb-b6dd-af867b2efb5d"
}
},
{
"model"
:
"workflows.abstractinput"
,
"fields"
:
{
"widget"
:
"09d72ebd-2eaf-47f6-95e0-2f2ed0c51ea2"
,
"name"
:
"Language"
,
"short_name"
:
"lan"
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workflows/nlp/package_data/widgets/1e75106f-ba4c-4b2b-a8cf-fb0f9c1d42f8.json
0 → 100644
View file @
901c3e49
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