def tokenize_sentence_words(tokenizer, sentence_words, sentence_word_tags):
	"""
	Tokenizes each word in a sentence using a given tokenizer (eg: BiobertTokenizer)
	For each word in the sentence, asociates its tag to the corresponding word tokens
	Inputs:
		tokenizer: the tokenizer used (eg: BiobertTokenizer)
		sentence_words: the sentence split into words, as a list
		sentence_word_tags: the tags associated with each of the words in sentence_words
	Outputs:
		sentence_tokenized: the sentence split into tokens, as a list
		sentence_tokenized_tags: the tags associated with each of the tokens in the sentence
	"""
	sentence_tokenized = []
	sentence_tokenized_tags = []

	for word_idx, word in enumerate(sentence_words):
		word_tokens = tokenizer.tokenize(str(word))
		word_tag = sentence_word_tags[word_idx]
		num_word_tokens = len(word_tokens)
		sentence_tokenized.extend(word_tokens)
		sentence_tokenized_tags.extend([word_tag] * num_word_tokens)
	return sentence_tokenized, sentence_tokenized_tags