Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Summadaynta Qayb-Hadal

Dib u eeg qaybaha POS, madmadowga guud, calaamadaha Penn Treebank, HMM kala-guurka iyo qiiqa, sifooyinka VBD, NLP, qaybaha UD, iyo xidhiidhada syntax.

Wadooyinka haga ee la xidhiidhaQayb ka mid ah hadalka hadalka
Su'aal 1 ee 8

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

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  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. Waa maxay sababta macnaha guud uu muhiim ugu yahay calaamadaynta POS?
    • Sababtoo ah eray kastaa wuxuu leeyahay hal sumad oo suurtagal ah
    • Sababtoo ah calaamadaynta waxay iska indhatiraysaa jumlada gabi ahaanba
    • Sababtoo ah jumladaha dhaadheer ayaa had iyo jeer fudud
    • Sababtoo ah ereyo badan ayaa noqon kara qaybo kala duwan oo hadal ah iyadoo ku xiran isticmaalka
  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?
    • Isku-buufinta faylka sawirka
    • Aqoonsiga cidda magacaaban
    • Audio amplifier volume control
    • Disk encryption
  7. How many universal POS categories does the stated Universal Dependencies version 2 inventory define?
    • Seventeen
    • Laba
    • 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