# viterbi.py
# ---------------
# Licensing Information:  You are free to use or extend this projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to the University of Illinois at Urbana-Champaign
#
# Created by Renxuan Wang (renxuan2@illinois.edu) on 10/18/2018

"""
This is the main entry point for MP5. You should only modify code
within this file -- the unrevised staff files will be used for all other
files and classes when code is run, so be careful to not modify anything else.
"""

'''
TODO: implement the baseline algorithm.
input:  training data (list of sentences, with tags on the words)
        test data (list of sentences, no tags on the words)
output: list of sentences, each sentence is a list of (word,tag) pairs. 
        E.g., [[(word1, tag1), (word2, tag2)], [(word3, tag3), (word4, tag4)]]
'''
def baseline(train, test):
    predicts = []
    return predicts

'''
TODO: implement the Viterbi algorithm.
input:  training data (list of sentences, with tags on the words)
        test data (list of sentences, no tags on the words)
output: list of sentences with tags on the words
        E.g., [[(word1, tag1), (word2, tag2)], [(word3, tag3), (word4, tag4)]]
'''
def viterbi(train, test):
    predicts = []
    return predicts
