The array has some issues. The main one is probably that it is malformed. I haven’t reviewed it from top to bottom but I can see at least one serious issue here right towards the beginning:
@”CHOPSTICKS”@”BALTHUS”
Where there is a comma missing between two elements. I was able to see this from the logging because this warning caught my eye:
The word CHOPSTICKSBALTHUS was not found in the dictionary
A good way for you to troubleshoot this would be to bisect: submit half of your array and if it works, check the other half. If it doesn’t work, find the half containing the part which doesn’t work, reducing by halves until you find the area there is an issue with. That will also let you show me a small reduced example case without so much logging output if the issue is actually a bug. Or stick to importing it from a text file.
It would be a good idea for you to review the logging output yourself as well as showing it to me, because there is important info in there which will heavily affect recognition accuracy of your grammar when there are warnings like this:
2015-01-21 19:30:41.843 [5710:802222] Now using the fallback method to look up the word & 2015-01-21 19:30:41.843 [5710:802222] If this is happening more frequently than you would expect, the most likely cause for it is since you are using the English phonetic lookup dictionary is that your words are not in English or aren’t dictionary words, or that you are submitting the words in lowercase when they need to be entirely written in uppercase. This can also happen if you submit words with punctuation attached – consider removing punctuation from language models or grammars you create before submitting them.
There are many warnings about phrases being submitted where there is punctuation as part of them which is attempted to be added to your dictionary, and also things like the letter “N” being added to the phonetic dictionary by itself due to a name written in slang. You should remove the punctuation other than apostrophes that are part of words before submitting the grammar to be created so it is possible for your users to say the names involved and have them recognized. Sometimes this requires cleaning up the input in ways that insure that the grammar and dictionary created are full of machine-recognizable entries.