MS-DS Master of Data science FREE Master of Data Science Natural Language Processing Questions and Answers 2

Question 1

Which technique represents words as dense, low-dimensional vectors learned from large corpora?

Accepted Answer

Word embeddings

Answer

Word embeddings like Word2Vec and GloVe learn dense vector representations that capture semantic relationships between words.

Question 2

What is the primary purpose of the attention mechanism in sequence-to-sequence models?

Accepted Answer

To allow the decoder to focus on relevant parts of the input sequence

Answer

Attention lets the decoder selectively weight different positions in the input sequence, improving performance on long sequences.

Question 3

In named entity recognition (NER), which label would typically be assigned to the word 'Stanford' in the sentence 'She studied at Stanford'?

Accepted Answer

Organization

Answer

Stanford refers to Stanford University, which is classified as an organization entity in standard NER tagging schemes.

Question 4

What problem does beam search address during text generation compared to greedy decoding?

Accepted Answer

It explores multiple candidate sequences to find a higher-probability output

Answer

Beam search maintains multiple partial hypotheses at each step, reducing the risk of selecting a locally optimal but globally suboptimal sequence.

Question 5

Which evaluation metric computes the geometric mean of n-gram precisions between generated and reference text?

Accepted Answer

BLEU

Answer

BLEU calculates precision for n-grams of various lengths and combines them using a geometric mean with a brevity penalty.

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