Not installing on ubuntu about redshift HOT 12 OPEN

The problem is that the requirements.txt file hasn't version pinned for the dependencies. I've updated/rewritten these libraries, and now redshift doesn't compile.

The offending change seems to be this one:

1487f64

Instead of updating the pin to the correct version, I removed the version pin. Damn.

To solve this, the correct versions need to be identified, and the versions specified in the requirements.txt

The following libraries need version pinning:

murmurhash
cymem
preshed
thinc

I've made lots of releases of thinc, and a couple of preshed. cymem and murmurhash have been more stable.

Looking through the commit history of thinc, and matching up the dates, it looks like v1.73 is a likely candidate.

from redshift.

Found the right versions. Now compiles for me. Give it a go.

Btw, just checking that you know that this library is code from my research, and that the maintained library is spaCy? Probably this library is only useful for replicating or extending one of my papers, especially the disfluency detection one. If you're doing that, let me know if you have any questions.

But if you're just looking for a good parsing library, try spaCy :). http://spacy.io

from redshift.

I tried installing it again. Gives me the following errors now
http://pastebin.com/7T7tV0xN

I just wanted a fast POS tagging utility. I was not aware of spaCy. Using that now. Thanks a lot for the quick reply :)

from redshift.

http://nlp.stanford.edu/software/tagger.shtml

On Fri, Dec 4, 2015 at 9:53 PM, pawanjay176 [email protected]
wrote:

I tried installing it again. Gives me the following errors now
http://pastebin.com/7T7tV0xN

I just wanted a fast POS tagging utility. I was not aware of spaCy. Using
that now. Thanks a lot for the quick reply :)

—
Reply to this email directly or view it on GitHub
#20 (comment).

from redshift.

spaCy's tagger is MIT licensed, can be used from Python, and is much faster than Stanford's :). Accuracy should be the same as well.

from redshift.

how can i use spaCy's or stanford for for parsing only for define noun and
verb ?.i want to send noun and verb in a database because i want to use it
search poses in a search engine .

On Fri, Dec 4, 2015 at 10:06 PM, Matthew Honnibal [email protected]
wrote:

spaCy's tagger can be used from Python, and is much faster than Stanford's
:). Accuracy should be the same as well.

—
Reply to this email directly or view it on GitHub
#20 (comment).

from redshift.

I'm not sure I understand your question. But this will load spaCy's default English model, analyse some text, and return only the nouns and verbs. The parser is here disabled for efficiency.

>>> from spacy.en import English
>>> from spacy.attrs import NOUN, VERB
>>> nlp = English(parser=False)
>>> doc = nlp(u'An example sentence, that has two nouns. This sentence contains three nouns.')
>>> print([w.text for w in doc if w.pos in (NOUN, VERB)]
[u'sentence', u'has', u'nouns', u'contains', u'nouns']

See the spaCy docs for details. You should ask further questions there as well :)

from redshift.

great....i want to make a search engine for my BSC final year project and
it is ontology base semantic search engine . it depends on verb . the main
class is verb for search and sub class in noun .so i need to define verb
and noun and search in a specific domain .
do you understand ,about my project . i really need parsing it for future
work .

On Fri, Dec 4, 2015 at 10:59 PM, Matthew Honnibal [email protected]
wrote:

I'm not sure I understand your question. But this will load spaCy's
default English model, analyse some text, and return only the nouns and
verbs. The parser is here disabled for efficiency.

from spacy.en import English
from spacy.attrs import NOUN, VERB
nlp = English(parser=False)
doc = nlp(u'An example sentence, that has two nouns. This sentence contains three nouns.')
print([w.text for w in doc if w.pos in (NOUN, VERB)]
[u'sentence', u'has', u'nouns', u'contains', u'nouns']

See the spaCy docs for details. You should ask further questions there as
well :)

—
Reply to this email directly or view it on GitHub
#20 (comment).

from redshift.

Thanks a ton!
Tagger is really accurate and way way fast than stanford tagger

from redshift.

but i do not understand how can i use it for search engine?can you kindly
describe it.plz

On Sat, Dec 5, 2015 at 1:03 AM, pawanjay176 [email protected]
wrote:

Thanks a ton!
Tagger is really accurate and way way fast than stanford tagger

—
Reply to this email directly or view it on GitHub
#20 (comment).

from redshift.

You can pos_tag any sentence like this

from spacy.en import English, LOCAL_DATA_DIR
import spacy.en
import os, time
data_dir = os.environ.get('SPACY_DATA', LOCAL_DATA_DIR)
nlp = English(parser=False, tagger=True, entity=False)

def print_fine_pos(token):
return (token.tag_)

def pos_tags(sentence):
sentence = unicode(sentence, "utf-8")
tokens = nlp(sentence)
tags = []
for tok in tokens:
tags.append((tok,print_fine_pos(tok)))
return tags

print pos_tags("This is a sentence")

from redshift.

how can i install spaCy.io in Ubuntu 14.04 ? i install Canopy before
.

On Sat, Dec 5, 2015 at 1:25 AM, pawanjay176 [email protected]
wrote:

You can pos_tag any sentence like this

from spacy.en import English, LOCAL_DATA_DIR
import spacy.en
import os, time
data_dir = os.environ.get('SPACY_DATA', LOCAL_DATA_DIR)
nlp = English(parser=False, tagger=True, entity=False)

def print_fine_pos(token):
return (token.tag_)

def pos_tags(sentence):
sentence = unicode(sentence, "utf-8")
tokens = nlp(sentence)
tags = []
for tok in tokens:
tags.append((tok,print_fine_pos(tok)))
return tags

print pos_tags("This is a sentence")

—
Reply to this email directly or view it on GitHub
#20 (comment).

from redshift.