written2-soln.pdf - CS-5340\/6340 Solutions to Written Assignment#2 DUE Thursday by 11:59pm Submit your assignment on CANVAS in pdf format 1(20 pts For

# written2-soln.pdf - CS-5340/6340 Solutions to Written...

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CS-5340/6340, Solutions to Written Assignment #2 DUE: Thursday, September 19, 2019 by 11:59pm Submit your assignment on CANVAS in pdf format. 1. (20 pts) For each sentence below, indicate whether the main verb appears in an intransitive construction, a transitive construction, or a ditransitive construction. Only give the answer transitive if the usage is not ditransitive . (a) She solved the puzzle in two minutes. TRANSITIVE (b) Tom has read ten books by Stephen King. TRANSITIVE (c) Lee cooked Mary a steak for her birthday. DITRANSITIVE (d) The boy dreamt about summer camp. INTRANSITIVE (e) The rabbit hopped up the stairs to its favorite room. INTRANSITIVE (f) Jim sneezes often during allergy season. INTRANSITIVE (g) Susan lent her brother some money for his tuition. DITRANSITIVE (h) Pat learned to ski by trial and error. INTRANSITIVE (i) A bird flew into the building. INTRANSITIVE 1
(j) The reporter investigated the story thoroughly and carefully. TRANSITIVE 2
2. (40 pts) Use the following tables of probabilities to answer this question. Note that these numbers are completely fictional and not necessarily realistic! P(California | NOUN) . 04 P(California | VERB) .008 P(seals | NOUN) .05 P(seals | VERB) .02 P(report | NOUN) .07 P(report | VERB) .06 P(NOUN | φ ) .75 P(VERB | φ ) .25 P(NOUN | NOUN) .30 P(VERB | NOUN) .50 P(Ω | NOUN) . 20 P(NOUN | VERB) . 55 P(VERB | VERB) . 35 P(Ω | VERB) .10 Assume that there are 2 possible part-of-speech tags: NOUN and VERB. The following network would be used by the Viterbi algorithm to find the most likely sequence of POS tags for the sentence “California seals report” : Ω report=NOUN seals=NOUN seals=VERB California=NOUN California=VERB φ report=VERB Using the Viterbi algorithm, compute the probability for each of the following nodes in the network. Show all your work! (a) P(California=NOUN) P ( NOUN | φ ) * P ( California | NOUN ) = .75 * .04 = . 03 (b) P(California=VERB) P ( V ERB | φ ) * P ( California | V ERB ) = .25 * .008 = . 002 (c) P(seals=NOUN) P ( seals | NOUN ) * MAX ( P ( NOUN | NOUN )*.03, P ( NOUN | V ERB )*.002) .05 * MAX[(.30 * .03), (.55 * .002)] = .05 * MAX[.009,.0011] = .00045 (d) P(seals=VERB) P ( seals | V ERB ) * MAX ( P ( V ERB | NOUN )*.03, P ( V ERB | V ERB )*.002) .02 * MAX[(.50*.03),(.35*.002)] = .02 * MAX[.015,.0007] = .0003 3
Using the same network, compute the forward probabilities

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