#!/usr/bin/env python -*- coding: utf-8 -*-
#
# Python Word Sense Disambiguation (pyWSD): Baseline WSD
#
# Copyright (C) 2014-2020 alvations
# URL:
# For license information, see LICENSE.md

import random
custom_random = random.Random(0)

def random_sense(ambiguous_word, pos=None):
    """ Returns a random sense. """
    if pos is None:
        return custom_random.choice(wn.synsets(ambiguous_word))
    else:
        return custom_random.choice(wn.synsets(ambiguous_word, pos))

def first_sense(ambiguous_word, pos=None):
    """ Returns the first sense. """
    if pos is None:
        return wn.synsets(ambiguous_word)[0]
    else:
        return wn.synsets(ambiguous_word, pos)[0]

def max_lemma_count(ambiguous_word):
    """
    Returns the sense with the highest lemma_name count.
    The max_lemma_count() can be treated as a rough gauge for the
    Most Frequent Sense (MFS), if no other sense annotated corpus is available.
    NOTE: The lemma counts are from the Brown Corpus
    """
    sense2lemmacounts = {}
    for i in wn.synsets(ambiguous_word):
        sense2lemmacounts[i] = sum(j.count() for j in i.lemmas())
    return max(sense2lemmacounts, key=sense2lemmacounts.get)

#!/usr/bin/env python -*- coding: utf-8 -*-
#
# Python Word Sense Disambiguation (pyWSD): Baseline WSD
#
# Copyright (C) 2014-2020 alvations
# URL:
# For license information, see LICENSE.md

import random
custom_random = random.Random(0)

def random_sense(ambiguous_word, pos=None):
    """ Returns a random sense. """
    if pos is None:
        return custom_random.choice(wn.synsets(ambiguous_word))
    else:
        return custom_random.choice(wn.synsets(ambiguous_word, pos))

def first_sense(ambiguous_word, pos=None):
    """ Returns the first sense. """
    if pos is None:
        return wn.synsets(ambiguous_word)[0]
    else:
        return wn.synsets(ambiguous_word, pos)[0]

def max_lemma_count(ambiguous_word, pos=None):
    """
    Returns the sense with the highest lemma_name count.
    The max_lemma_count() can be treated as a rough gauge for the
    Most Frequent Sense (MFS), if no other sense annotated corpus is available.
    NOTE: The lemma counts are from the Brown Corpus
    """
    sense2lemmacounts = {}
    for i in wn.synsets(ambiguous_word, pos=None):
        sense2lemmacounts[i] = sum(j.count() for j in i.lemmas())
    return max(sense2lemmacounts, key=sense2lemmacounts.get)

Add pos for max_lemma_count also
Add pos for max_lemma_count also
