I hand crafted some training data for NLP tasks on Turkish with Arabic-script. There has been almost nothing done in that area until now.

Motivation

There are millions of documents remain to be discovered from Ottoman times in Turkey. They might change the known history. There are not many people who can work on these documents.

It all starts with the decision of migrating to Latin-script back in 1928 by the new established Turkish government. Then efforts in this area are crippled : people are forced to forget the Arabic-script.

Today it is vice versa : new government encouraging learning the Turkish written in Arabic-script. However, there is too little scientific effort in this area.

My project’s purpose is to provide some initial training data for the NLP tasks on Turkish in Arabic-script. This is just a baby step in this area.

Document

I chose a document written in Arabic-script and annotated the words in it. Every annotation has the digital Arabic-script and Latin-script Turkish word.

Ironically, the document I chose is the book used in primary schools to teach reading and writing to children.

Process and technical properties

Here is how I proceeded:

  1. Convert source document to JPGs
  2. Display JPGs and annotate areas
  3. Write annotations to a plain text file

Annotation is done with a web UI. It is Html canvas where user can select a rectangular area. When the area is selected, user types the Arabic-script word and Latin-script word.

I chose storing the data as plain text to have a flat structure. Being flat is really important since you can manually modify the file easily and diff is intuitive.

Result

Training data I prepared is the files in here : https://github.com/aliok/osmani/tree/master/data/src/main/data/book-annotation

It has 4741 words in it including the punctuation. Around 30% of the words in it are unique.

Project is hosted on Github.

Future

I hope to work on this subject again in the future. Currently, the Government Archive Department is running a project to digitalize the archives. By that, I mean they’re scanning the documents to make them available online.

When that is done, I think we, computer scientists and software engineers, can build a platform to extract data out of them.