For the 428000-word Corpus of News, following counts of unigrams and bigrams are given as: Our-80000; motive- 40000; attack-21; our motive 378; our attack- 0. a) Estimate the probabilities P(our) and...


For the 428000-word Corpus of News, following counts of unigrams and bigrams are<br>given as:<br>Our-80000; motive- 40000; attack-21; our motive 378; our attack- 0.<br>a) Estimate the probabilities P(our) and P (motive | our) using Maximum<br>Likelihood estimation.<br>b) Discuss the challenge associated with bigram probability of P (attack | our) and<br>use the above given data to prove the solution numerically.<br>S-> NP VP<br>S-> VP<br>PropNoun -> DALLAS 0.2<br>PropNoun -> ALICE<br>0.4 PropNoun -> BOB<br>0.6<br>0.4<br>0.2<br>NP -> NP PP<br>0.3<br>NP -> PropNoun 0.6 PropNoun -> AUSTIN 0.3<br>VP -> Verb<br>0.3<br>Verb -> ADORE<br>0.5<br>VP -> Verb NP<br>0.3<br>Verb -> SEE<br>0.5<br>Prep -> IN<br>Prep -> WITH<br>VP -> VP PP<br>0.4<br>0.4<br>PP -> Prep NP<br>1.0<br>0.6<br>

Extracted text: For the 428000-word Corpus of News, following counts of unigrams and bigrams are given as: Our-80000; motive- 40000; attack-21; our motive 378; our attack- 0. a) Estimate the probabilities P(our) and P (motive | our) using Maximum Likelihood estimation. b) Discuss the challenge associated with bigram probability of P (attack | our) and use the above given data to prove the solution numerically. S-> NP VP S-> VP PropNoun -> DALLAS 0.2 PropNoun -> ALICE 0.4 PropNoun -> BOB 0.6 0.4 0.2 NP -> NP PP 0.3 NP -> PropNoun 0.6 PropNoun -> AUSTIN 0.3 VP -> Verb 0.3 Verb -> ADORE 0.5 VP -> Verb NP 0.3 Verb -> SEE 0.5 Prep -> IN Prep -> WITH VP -> VP PP 0.4 0.4 PP -> Prep NP 1.0 0.6

Jun 03, 2022
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