पार्ट-ऑफ़-स्पीच टैगिंग क्विज़

जैसे ही आप प्रश्नोत्तरी लेते हैं उत्तर और स्पष्टीकरण दिखाई देते हैं।

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. पीओएस टैगिंग के लिए संदर्भ क्यों आवश्यक है?
   • क्योंकि प्रत्येक शब्द में बिल्कुल एक संभावित टैग होता है
   • क्योंकि टैगिंग वाक्य को पूरी तरह से नजरअंदाज कर देती है
   • क्योंकि लंबे वाक्य हमेशा आसान होते हैं
   • क्योंकि कई शब्द उपयोग के आधार पर भाषण के विभिन्न भाग हो सकते हैं
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?
   • छवि फ़ाइल संपीड़न
   • नामित-इकाई पहचान
   • Audio amplifier volume control
   • Disk encryption
7. How many universal POS categories does the stated Universal Dependencies version 2 inventory define?
   • Seventeen
   • दो
   • 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