As per the StanfordCoreNLP documentation for CoreLabel, The functions after() and before() should return white space strings between the token and the next/previous tokens respectively.
However, they return an empty string always even if there are some white spaces when the tokenizer option **normalizeOth

We should do a benchmark against existing implementations of LDA (like Mallet) for sanity.

../../const.go:58: constant 1000000000000 overflows int
../../const.go:59: constant 1000000000000000 overflows int

Tasks

• Create a version of const.go for ARM that doesn't have those two numbers
• ALTERNATIVE SOLUTION: use int64 for NumberWords

In a sentence with an uppercase word in the middle, if the uppercase word is correctly tagged as a common noun, Talismane will not find its lemma in the glossary, because the common noun entry is in lowercase. Need to make the lemma search case-insensitive.