I am currently working on my last project before graduating. For this project, I have to develop a Natural Language Question Answering System. Now, I have read quite some research papers regarding this topic and have figured out everything except for the parsing algorithm.
The NL Q-A will be programmed in Python, and I will use the spaCy library to finish this project. However, I am stuck when it comes to parsing algorithms. I managed to reduce the parsing algorithms to 3:
- Cocke-Kasami-Younger (CKY) algorithm
- Earley algorithm
- Chart Parsing algorithm
Note: I know that all three algorithms are chart parsing algorithms. I also know that the Earley algorithm is context-free, but has a low efficiency for a compiler.
What I don't know is: Which one should I pick? (non-subjective answer to this question)
The system is for a specific domain. And the answer of the natural question will be displayed in the form of the result of a calculation of some kind. Preferably in the tabular or graphical form.
Furthermore, I have done my research. However, I probably do not understand the algorithms properly, which makes it difficult to make a selection. The algorithm should be efficient and perhaps outperform others. (You are my last hope!)