English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Semantic parsing is the task of mapping natural language to logic form. Inquestion answering, semantic parsing can be used to map the question to logicform and execute the logic form to get the answer. One key problem for semanticparsing is the hard label work. We study this problem in another way: we do notuse the logic form any more. Instead we only use the schema and answer info. Wethink that the logic form step can be injected into the deep model. The reasonwhy we think removing the logic form step is possible is that human can do thetask without explicit logic form. We use BERT-based model and do the experimentin the WikiSQL dataset, which is a large natural language to SQL dataset. Ourexperimental evaluations that show that our model can achieves the baselineresults in WikiSQL dataset.

Table2answer: Read the database and answer without SQL