First, be careful of response ottion #6. You will want to treat that as missing data (or some other option) since it is not part of the disagree->agree response pattern. From there you can analyze the correlations directly, e.g., in R: cor.test(x,y,method="spearman")

There is a difference between items that use Likert-scoring (such as you describe) versus scales that are composed multiple items with LIkert-scoring. I would recommend assess the possibility of creating an interval level scale from your 5 items, starting with an assessment of Cronbach's alpha.

Because there have been so many questions here about Likert-score items and scales, I have collected a set of resources on this topic:

https://www.researchgate.net/post/How_can_one_help_people_create_simple_scales_from_Likert-scored_items

 Dear Alisi

I agree with the comment of David, and there is another question in researchgate ( but for Pearson ) have many useful comments, I hope you can read them in the link:

https://www.researchgate.net/post/How_can_I_make_a_correlation_Pearson_using_a_Likert_Scale

Good Luck

Most Likert scales are composed from items with 5 to 7 steps rating. The original authors of those scales usually state how to score the scale/subscales {if present}. To take benefit from Likert scales in inferential statistics, researchers use the sum of scores, which convert the scale from ordinal to ratio level of measurement. 

However, it is acceptable practice to work with the individual items in descriptive and non-parametric statistics.

The main issue in the case which you presented, is option # 6 {NA}, so either you have consider it as missing or see the original guide from the author.