# Is it possible to find uncertainties of spaCy POS tags?

**URL:** <https://support.prodi.gy/t/is-it-possible-to-find-uncertainties-of-spacy-pos-tags/3719>\
**Category:** Uncategorized\
**Tags:** spacy, pos, off-topic\
**Created:** [December 9, 2020, 6:00pm UTC](https://support.prodi.gy/t/is-it-possible-to-find-uncertainties-of-spacy-pos-tags/3719 "2020-12-09T18:00:41Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Joeytje50](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/joeytje50/32/1806_2.png) [@Joeytje50](https://support.prodi.gy/u/Joeytje50)\
**Post date:** [December 9, 2020, 6:00pm UTC](https://support.prodi.gy/t/is-it-possible-to-find-uncertainties-of-spacy-pos-tags/3719/1 "2020-12-09T18:00:41Z")

</div>

(originally posted on [https://stackoverflow.com/questions/65218606/is-it-possible-to-find-uncertainties-of-spacy-pos-tags](https://stackoverflow.com/questions/65218606/is-it-possible-to-find-uncertainties-of-spacy-pos-tags))

I am looking for a way to figure out the probabilities of certain tags set by spacy. So far, with some help from StackOverflow, I got to the following piece of code:

```
import spacy

nlp = spacy.load('en_core_web_sm')
text = "This is an example sentence for the Spacy tagger."
doc = nlp(text)

docs = nlp(text, disable=['tagger'])
scores, tensors = nlp.tagger.predict([docs])

print(scores)
probs = tensors[0]
for p in probs:
    print(p, max(p), p.tolist().index(max(p)))

```

Now this outputs a long list of numbers (96 of them, in this case) that look like probabilities, but I have no idea what these numbers mean exactly, and I have no idea how I can then turn this into an actual tag and the uncertainty attached to that tag. Is there any resource I can check to find what these numbers mean?