Preparing training data for a domain with many multi keyword token

How do I prepare the training data if I have many multi word token in domain like chemistry. For example:

**1. Original Sentences:** "This is a multi word chemical component 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide. \n This is another sentence."

Here "3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide" is a single token. There are multiple words inside the token which are white space separated. This would lead to the above token to be split as 3 tokens: ['3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl','tetrazolium', 'bromide'].

How can I avoid this? Can I give the input training data in the following format to avoid this?

**Training data(1) :** List of tokens for each sentences. So the training text file will have list of list tokens.

[['This', 'is', 'a', 'multi', 'word', 'chemical', 'component', '3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide'], ['This', 'is', 'another', 'sentence.']]

**Training data(2):** Here I have concatenated the multi keyword token by '|' symbol.
"This is a multi word chemical component 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl|tetrazolium|bromide. \n This is another sentence." Then I tweak the ELMO code to handle the | symbol and retain them as a single token.

Please guide on the best way to prepare the training data.