You want to compute the Levenshtein distance between two sentences by treating each word as a token. Which method correctly applies the Levenshtein distance in this context?

hard📝 Application Q8 of 15

NLP - Text Similarity and Search

ATokenize both sentences into word lists and compute Levenshtein distance treating each word as a single element

BCompute Levenshtein distance on the concatenated characters of both sentences without tokenization

CCalculate Levenshtein distance only on the first words of each sentence

DUse Levenshtein distance on the sentences after removing all spaces

Step-by-Step Solution

Solution:

Step 1: Understand token-level Levenshtein
To compare sentences word-by-word, tokenize into word lists.
Step 2: Apply Levenshtein on tokens
Compute distance treating each word as a token, not characters.
Step 3: Analyze options
Tokenize both sentences into word lists and compute Levenshtein distance treating each word as a single element correctly describes this approach. Others ignore tokenization or treat characters incorrectly.
Final Answer:
Option A -> Option A
Quick Check:
Tokenize sentences before applying Levenshtein for word-level distance. [OK]

Quick Trick: Tokenize sentences into words before distance calculation [OK]

Common Mistakes:

MISTAKES

Applying character-level distance directly on sentences
Ignoring tokenization step

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More NLP Quizzes

You want to compute the Levenshtein distance between two sentences by treating each word as a token. Which method correctly applies the Levenshtein distance in this context?

Step 1: Understand token-level Levenshtein

Step 2: Apply Levenshtein on tokens

Step 3: Analyze options

Final Answer:

Quick Check:

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