Below is a list of topics that can be considered as a course project.

1. Evaluation project. Evaluate one or more parsers. Here you have to decide which language(s) you are interested in, what type of text domain, and what type of evaluation you will perform.
2. Implement a parser/parser component. One option is to use one or more of the VG tasks in assignment 1 as a starting point, and considerably extend it/them. Note that the project should not overlap with the VG task you might have done. You may also consider implementing Earley's algorithm. It is also possible to come up with another plan for implementing a parser or parser component.
3. Treebank transformations. Investigate the effect of different types of treebank transformations on parsing.
4. Feature engineering for dependency parsing. Investigate the effect of different types of features used for learning the best transitions in a dependency parser, for example MaltParser.
5. Extended literature survey of modern phrase structure and/or dependency parsing. Here you should investigate several state-of-the-art proposals for parsing, by reading several articles from recent years (approximately 2015--present).
6. your own topic.

You are welcome to use datasets that were introduced during the course. You can also consider using the existing tools such as Indri or Lucene toolkit for indexing and searching in a large text corpus; using Stanford NLP parser or, NLTK or OpenNLP toolkits for text analysis; using MALLET or WEKA for classification or clustering.