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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Systematic comparison of methods for relation extraction (RE) is difficultbecause many experiments in the field are not described precisely enough to becompletely reproducible and many papers fail to report ablation studies thatwould highlight the relative contributions of their various combinedtechniques. In this work, we build a unifying framework for RE, applying thison three highly used datasets (from the general, biomedical and clinicaldomains) with the ability to be extendable to new datasets. By performing asystematic exploration of modeling, pre-processing and training methodologies,we find that choices of pre-processing are a large contributor performance andthat omission of such information can further hinder fair comparison. Otherinsights from our exploration allow us to provide recommendations for futureresearch in this area.

REflex: Flexible Framework for Relation Extraction in Multiple Domains