- Character Detector : Used a combination of both traditional NER (NLTK) and neural net pretrained NER (spacy) to detect all possible characters incase any -one of them missed out some entity.
- Character Recogniser : To understand the characters and related context, find all mentions/expressions in the summary and link the pronouns with their nouns (Coreference Resolution).
- Here we extract dialogue from the script for each character and convert it into the corresponding vector using word2vec. You need to download this file to use the word2vec model
- We finetune GPT2 using data from imsdb. We use the imsdb_scrapper for scraping the data from the website.
- Example of using Finetuned GPT2 to generate scripts from summary