Annotate func will be very very slow if input a wrong propertity

[eliasyin]

In my Case, if I input a wrong property paramater, the annotate func will be very slow. I think a wrong param detection should be added

import re
from stanfordcorenlp import StanfordCoreNLP
nlps = StanfordCoreNLP(
    r'./stanford-corenlp-full-2018-02-27')
text = 'golf and rugby union sevens get the nod for rio olympics in 2016 : • tiger woods says he hopes to compete in bra . .'
text = re.sub(r'\. ', ' .', text).strip()
text = re.sub(r' {2,}', ' ', text)
nlp_properties = {
    'annotatiors' : "depparse",   
# Right param is :   'annotators' : "depparse", 
    'tokenize.whitespace' : True,
    'ssplit.isOneSentence' : False,
    'outputFromat' : 'json'
}
nlps.annotate(text.strip(), nlp_properties)

[AngledLuffa]

It's non-trivial to add error checking, since user annotators could always need otherwise unknown properties

On Thu, Nov 12, 2020 at 12:12 AM eliasyin notifications@github.com wrote:

In my Case, if I input a wrong property paramater, the annotate func will be very slow. I think a wrong param detection should be added

import re from stanfordcorenlp import StanfordCoreNLP nlps = StanfordCoreNLP(

r'./stanford-corenlp-full-2018-02-27')

text = 'golf and rugby union sevens get the nod for rio olympics in 2016 : • tiger woods says he hopes to compete in bra . .' text = re.sub(r'. ', ' .', text).strip() text = re.sub(r' {2,}', ' ', text) nlp_properties = {

'annotatiors' : "depparse",

Right param is : 'annotators' : "depparse",

'tokenize.whitespace' : True,

'ssplit.isOneSentence' : False,

'outputFromat' : 'json'

} nlps.annotate(text.strip(), nlp_properties)

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[eliasyin]

fine