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.