Mit dem Guide verknüpftes Quiz · Mittel Ebene

Teil-of-Speech-Tagging-Quiz

Überprüfen Sie POS-Kategorien, kontextuelle Mehrdeutigkeit, Penn Treebank-Tags, HMM-Übergänge und -Emissionen, VBD, NLP-Funktionen, UD-Kategorien und Syntaxbeziehungen.

Verwandte FührungspfadePart-of-Speech-Tagging
Frage 1 von 8

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

Sehen Sie sich jede Frage in der Vorschau an8 Fragen

Während Sie am Quiz teilnehmen, werden Antworten und Erklärungen angezeigt.

  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. Warum ist der Kontext für das POS-Tagging so wichtig?
    • Denn jedes Wort hat genau ein mögliches Tag
    • Weil das Markieren den Satz völlig ignoriert
    • Denn längere Sätze sind immer einfacher
    • Denn viele Wörter können je nach Verwendung unterschiedliche Wortarten sein
  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?
    • Bilddateikomprimierung
    • Erkennung benannter Entitäten
    • Audio amplifier volume control
    • Disk encryption
  7. How many universal POS categories does the stated Universal Dependencies version 2 inventory define?
    • Seventeen
    • Zwei
    • 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