☛ What is part of speech (POS) tagging? What is the simplest approach to building a POS tagger that you can imagine?

☛ How would you build a POS tagger from scratch given a corpus of annotated sentences? How would you deal with unknown words?

☛ How would you train a model that identifies whether the word “Apple” in a sentence belongs to the fruit or the company?

☛ How would you find all the occurrences of quoted text in a news article?

☛ How would you build a system that auto corrects text that has been generated by a speech recognition system?

☛ What is latent semantic indexing and where can it be applied?

☛ How would you build a system to translate English text to Greek and vice-versa?

☛ How would you build a system that automatically groups news articles by subject?

☛ What are stop words? Describe an application in which stop words should be removed.

☛ How would you design a model to predict whether a movie review was positive or negative?

☛ What is entropy? How would you estimate the entropy of the English language?

☛ What is a regular grammar? Does this differ in power to a regular expression and if so, in what way?

☛ What is the TF-IDF score of a word and in what context is this useful?

☛ How does the PageRank algorithm work?

☛ What is dependency parsing?

☛ What are the difficulties in building and using an annotated corpus of text such as the Brown Corpus and what can be done to mitigate them?

☛ What tools for training NLP models (nltk, Apache OpenNLP, GATE, MALLET etc…) have you used?

☛ Do you have any experience in building ontologies?

☛ Are you familiar with WordNet or other related linguistic resources?

☛ Do you speak any foreign languages?