DSE Natural Language Processing Fundamentals 3

Question 1

What is the primary difference between stemming and lemmatization?

Accepted Answer

Stemming applies heuristic rules while lemmatization returns valid base dictionary forms

Answer

Stemming uses rule-based chopping of word endings, while lemmatization uses morphological analysis to return proper base forms.

Question 2

In sentiment analysis, what is the challenge of handling negation in sentences like 'not good'?

Accepted Answer

Bag-of-words models miss the interaction between 'not' and 'good'

Answer

Simple bag-of-words models treat words independently, so 'not' and 'good' are scored separately rather than as an inverted sentiment unit.

Question 3

Which technique allows a pre-trained language model to perform a new NLP task with only a few examples provided in the input prompt?

Accepted Answer

Few-shot prompting

Answer

Few-shot prompting provides the model with a small number of input-output examples in the prompt, enabling task performance without gradient updates.

Question 4

What does TF-IDF measure in document representation?

Accepted Answer

The importance of a term in a document relative to a corpus

Answer

TF-IDF weights terms by how often they appear in a document (TF) discounted by how common they are across all documents (IDF).

Question 5

In dependency parsing, what does a dependency arc represent?

Accepted Answer

A directed grammatical relationship between a head word and a dependent word

Answer

Dependency arcs connect a head word to its grammatical dependent, labeled with the type of syntactic relation (e.g., subject, object).

DSE - Data Science Practice Test