Stanza-based morphological analysis for English, using universal features (UD)
Analysis citation
Språkbanken Text (2022). sbx-eng-msd-stanza-ufeats (updated: 2022-08-10). [Analysis]. Språkbanken Text. https://doi.org/10.23695/9bd6-bg35
Additional ways to cite the dataset.
Example
This analysis is used with Sparv. Check out Sparv's quick start guide to get started!
To use this analysis, add the following line under export.annotations in the Sparv corpus configuration file:
- <token>:stanza.ufeats # Universal morphological features
In order to use this annotation you need to add the following setting to your Sparv corpus configuration file:
metadata:
language: eng
For more info on how to use Sparv, check out the Sparv documentation.
Example output:
<token ufeats="Number=Sing|PronType=Dem">This</token>
<token ufeats="Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin">is</token>
<token ufeats="Definite=Ind|PronType=Art">a</token>
<token ufeats="Number=Sing">corpus</token>
<token>.</token>
Other references
Stanza: Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton and Christopher D. Manning. 2020
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages. In Association for Computational Linguistics (ACL) System Demonstrations. 2020