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

Only a year ago, all state-of-the-art coreference resolvers were using anextensive amount of surface features. Recently, there was a paradigm shifttowards using word embeddings and deep neural networks, where the use ofsurface features is very limited. In this paper, we show that a simple SVMmodel with surface features outperforms more complex neural models fordetecting anaphoric mentions. Our analysis suggests that using generalizedrepresentations and surface features have different strength that should beboth taken into account for improving coreference resolution.

Use Generalized Representations, But Do Not Forget Surface Features