-
Type:
Bug
-
Status: Open
-
Priority:
Major
-
Resolution: Unresolved
-
Affects Version/s: None
-
Fix Version/s: None
-
Component/s: language model
-
Labels:
-
Environment:Windows Server 2016, R version 3.3.3
-
Flags:Important
Came across an issue for identifying words in a sentence. For words such as can't, the tokenization using openNLP yields two words: "ca" and "n't"
As an example (captured in the screenshot), see the tokenization for the string
When heard the Xenogears soundtrack, so can't really describe.
Note the words marked by ID's 9 and 10 in the openNLP-output.png file.
Not sure if I am missing any parameters that would produce the correct result?
Would appreciate any ideas/community's attention to this issue. Thanks.