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품사 태깅 퀴즈

POS 카테고리, 문맥적 모호성, Penn Treebank 태그, HMM 전환 및 방출, VBD, NLP 기능, UD 카테고리 및 구문 관계를 검토합니다.

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질문 1 의 8

Which type of annotation does POS tagging assign to a token in context?

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  1. Which type of annotation does POS tagging assign to a token in context?
    • A document-level spam label only
    • A grammatical category such as noun, verb, or adjective
    • A translation into a required target language
    • A guarantee of the token's real-world referent
  2. POS 태깅에 컨텍스트가 필수적인 이유는 무엇입니까?
    • 모든 단어에는 정확히 하나의 가능한 태그가 있기 때문에
    • 태깅은 문장을 완전히 무시하기 때문에
    • 긴 문장이 항상 더 쉽기 때문입니다
    • 많은 단어들이 사용법에 따라 품사가 달라질 수 있기 때문에
  3. How should the core Penn Treebank POS inventory be distinguished from its additional punctuation annotations?
    • It contains exactly two labels and no punctuation annotations
    • It is a database containing only book reviews
    • It has 36 core POS tags, with punctuation tags also used
    • It provides a different trained neural model for every tag
  4. Which probabilities does a classic HMM POS tagger combine when scoring a tag sequence?
    • Tag-to-tag transitions and word emissions given tags
    • Only word filenames and image brightness
    • Only probabilities of a tag given a word with no sequence model
    • A requirement that every tag have equal probability
  5. In the Penn Treebank POS convention, which grammatical property does VBD mark?
    • A singular noun
    • An adjective
    • A coordinating conjunction
    • A past-tense verb
  6. Which language-processing experiment can use POS tags as additional input features?
    • 이미지 파일 압축
    • 명명된 엔터티 인식
    • Audio amplifier volume control
    • Disk encryption
  7. How many universal POS categories does the stated Universal Dependencies version 2 inventory define?
    • Seventeen
    • 2개
    • Thirty-six core Penn categories
    • One hundred compulsory English-only categories
  8. In Universal Dependencies, how does NOUN differ from nsubj?
    • Both are required names for the same trained model
    • NOUN marks sentence sentiment; nsubj marks image size
    • NOUN is a word category; nsubj is a nominal-subject relation
    • Both necessarily mean that a word is a past-tense verb