Context I decided, for a little hobby project I'm working on, that I needed a dialog dataset, which Cornell University kindly provided [here][1]. However, as a database programmer, I'm used to working with structured data, not parsing and building lists from text-based files, and I decided that life would be much easier for me if I had this data in an SQL-type database, so I wrote me a little python script to chunk the whole thing into SQLite. Content Original Data Set: https://www.kaggle.com/Cornell-University/movie-dialog-corpus As of this writing, the original dataset was updated 7 months ago. The data is normalized, with all of the code-breaking artifacts I ran into hand-corrected. If you're familiar with SQL, and have a language/library that supports SQLite, I hope you'll find this fairly easy to work with. All of the data from the original dataset is, I believe, present, though I did remove some redundancies. For example, in the original dataset, movie_lines.tsv lists the character name along with the character id, which is redundant, because the name is listed in the movie_characters.tsv file. While this is a convenience when you have to process the file directly, it can easily be obtained by a JOIN in a structured database. The raw_script_urls are included in the movies table. Acknowledgements Thank you to Cornell University for providing the original Corpus. Photo by Tobias Fischer on Unsplash Inspiration Do let me know if you find this useful. I will probably do similar conversions for other datasets as I need them, and would happily upload them if anyone else finds them useful in that form. [1]: https://www.kaggle.com/Cornell-University/movie-dialog-corpus