How and When features are attached to target label
I assume you're training a CRF model, or some other variant of sequence labeling, right? 

I'm not especially familiar with Mallet but it's very unlikely that any model would let you add features at testing stage: the trained model and the test data must have exactly the same features, no more no less.

Apparently the features you want to add consist of a similarity score with a few particular categories, I assume this score is calculated independently during pre-processing? If yes this would usually be represented like this in the data:

&lt;token&gt;   &lt;PLACE_LIKE&gt; &lt;CITY_LIKE&gt; &lt;COUNTRY_LIKE&gt; &lt;label&gt;
KFC       1.0          0.0         0.0            PLACE
Bangalore 0.0          1.0         0.0            CITY
INDIA     0.0          0.0         1.0            COUNTRY


Note that this format with token + N features must be followed in both the training and test data. Therefore you must apply the same pre-processing steps for both.