1. we need to extract the english title of the patent and add it to patents table.
  Done; actually it was very easy.
2. we need to extract only first character and following two digits from <classification-ipcr> tag e.g., A01 rather than A01B. This represents the class of the patent while extra chars/digits are subclasses and groups/subgroups which we don't need.
  Done.

3. we need to make sure each class is extracted only once per patent as I noticed they repeat at least twice in the document. If you think this will slow down parsing, we can merge them later in the DB.
  Done. In fact, it took less code than the previous solution.

4. we need to exctract the whole abstract tag. Sometimes you might encounter tags like <img> between <abstract> and </abstract> and this is not handled in the code. You might extract all text between opening and closing abstract tags then drop any tags in between.
  Fixed (I raised the target length for abstract to 2^64 - 1)

5. Is there any patents with description in the dataset? I couldn't locate any in the DB!
   This was an unfortunate sampling artifact. There are several long runs with foreign patents, and the sample I took was one of them.
Merge branch 'master' of https://github.com/SeanTater/patent-classification