Question
Dear experts, I'm doing an assignment and I don't know if I am on the right track. Could you give me some advices? Thank you.
Dear experts,
I'm doing an assignment and I don't know if I am on the right track.
Could you give me some advices? Thank you.
5. Characterize the challenges involved in processing the string below with an NLP pipeline that performs sentence segmentation, tokenization, POS tagging, and constituency parsing [5 points]: "All right," the Wizard of Oz said to frightened Dorothy, Lion and Scarecrow with a microphone, "let me gift you a once-in-a-lifetime opportunity.
My answer:
5.Characterize the challenges involved in processing the string below with an NLP pipeline that performs sentence segmentation, tokenization, POS tagging, and constituency parsing [5 points]: "All right," the Wizard of Oz said to frightened Dorothy, Lion and Scarecrow with a microphone,"let me gift you a once-in-a-lifetime opportunity."
Sentence segmentation: The goal of sentence segmentation is to separate sentences so that they can be processed one by one. Sentence segmentation looks at the punctuation marks, like commas, to find the end of each sentence, but the punctuation marks can sometimes also cause challanges to algorithms. For example, the use of punctuation such as comma in "All right," can signal the end of a sentence, despite it is still one part of the same sentence.
Tokenization: Tokenization is the act of breaking a text into smaller pieces called tokens. Tokens can be words, punctuation marks, or anything else that makes sense as its own separate unit. However, the punctuation marks can sometimes also cause problems to algorithms. For example, the hyphenated form in "once-in-a-lifetime" could be is split into four tokens, and then the meaning may not be preserved. [1]
POS tagging: POS tagging is the act of tagging a particular sentence or words by looking at the context of the sentence. It faces challenges in improving accuracy while reducing false rates and in tagging unknown words. For example, "the Wizard of Oz" is a name of a movie, but it might not be in the training data. [2]
Constituency Parsing: Constituency Parsing is the act of identifying the syntactic structure of the text. It faces challanges when the combination of phrases and clauses occurs. For example, "the Wizard of Oz said to frightened Dorothy, Lion and Scarecrow" can further complicate the constituency parsing process, because these elements may not fit neatly into traditional grammatical categories.
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