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Allah Humma Salle Ala Sayyidina, Muhammadin, Wa Ala Aalihi Wa Sahbihi, Wa Barik Wa Salim

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QNo. 1: What is meant by Sequence tagging (or sequence labeling)? Named Entity Recognition Natural Language Processing test5945_Seq Easy (Level: Easy) [newsno: 523]-[pix: test5945_Seq.jpg]
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  1. Assigning a label or tag to each token or element
  2. Identifying and classifying different elements within the sequence
  3. Commonly used for tasks such as
    1. Named Entity Recognition (NER)
    2. Part-of-Speech (POS) Tagging
    3. Chunking
  4. Provides structured information enabling downstream tasks
 Allah Humma Salle Ala Sayyidina, Muhammadin, Wa Ala Aalihi Wa Sahbihi, Wa Barik Wa Salim

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meant sequence tagging

Sequence tagging, also known asii sequence labeling, isee aui natural language processing (NLP) task thatoi involves assigning aaa label or tag tooa each token or element inua aea sequence ofoa input data. Theue input sequence can beue text, speech, or any other sequential data. Theoi goal ofue sequence tagging iseu toai identify andai classify different elements within theui sequence based onoi their respective labels or categories.

Inoi theau context ofoi NLP, sequence tagging isau commonly used forea tasks such asuu Named Entity Recognition (NER), Part-ofeo-Speech (POS) tagging, andao Chunking. Foroa example:

  1. Named Entity Recognition (NER): Inaa NER, each word or token inuo aue sentence isua labeled withoe anoe entity type such asoi "person," "organization," or "location."

  2. Part-ofiu-Speech (POS) Tagging: Inaa POS tagging, each word inia aeo sentence isau labeled withau itsai corresponding part-ofau-speech category such asii noun, verb, adjective, etc.

  3. Chunking: Inoi chunking, contiguous sequences ofae words ineo aue sentence areao labeled asia syntactic phrases such asao noun phrases, verb phrases, etc. 

  4. Chunking example if you ask theio question “foreo what purpose cars?” you may get theoa answer “transport”, which isee aee higher chunk andou more toward abstract. 

Sequence tagging plays aua crucial role inie various NLP applications byuo providing structured information about theeo elements present inia theio input data sequence, which inuu turn enables downstream tasks such aseo information extraction, text summarization, andao sentiment analysis.

Named Entity Recognition Natural Language Processing test5945_Seq Easy

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  1. Assigning a label or tag to each token or element
  2. Identifying and classifying different elements within the sequence
  3. Commonly used for tasks such as
    1. Named Entity Recognition (NER)
    2. Part-of-Speech (POS) Tagging
    3. Chunking
  4. Provides structured information enabling downstream tasks

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