Word prediction annotations for each word in a text.
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>:sbx_word_prediction_kb_bert.word-prediction--kb-bert # Word predictions from masked BERT (format: '|<word>:<score>|...|)
You also need to install the following plugin: sbx_word_prediction_kb_bert.
For general information on how to install plugins, see here.
For more info on how to use Sparv, check out the Sparv documentation.
Example output:
<token word="Engelbert" word-prediction--kb-bert="|Jag:0.388|Vi:0.384|Han:0.082|De:0.031|Hon:0.022|" pos="PM">Engelbert</token>
<token word="tar" word-prediction--kb-bert="|tar:0.541|tog:0.208|kör:0.157|körde:0.050|åker:0.004|" pos="VB">tar</token>
<token word="Volvon" word-prediction--kb-bert="|tunnelbanan:0.275|oss:0.118|bussen:0.116|mig:0.100|bilen:0.099|" pos="PM">Volvon</token>
<token word="till" word-prediction--kb-bert="|till:0.897|från:0.038|mot:0.028|på:0.009|förbi:0.007|" pos="PP">till</token>
<token word="Tele2" word-prediction--kb-bert="|Friends:0.584|Stockholm:0.136|Globen:0.037|Djurgården:0.034|Stockholms:0.027|" pos="PM">Tele2</token>
<token word="Arena" word-prediction--kb-bert="|arena:0.518|Arena:0.471|,:0.002|Globen:0.001|Stockholm:0.001|" pos="PM">Arena</token>