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

We investigate the less-explored task of generating open-ended questions thatare typically answered by multiple sentences. We first define a new questiontype ontology which differentiates the nuanced nature of questions better thanwidely used question words. A new dataset with 4,959 questions is labeled basedon the new ontology. We then propose a novel question type-aware questiongeneration framework, augmented by a semantic graph representation, to jointlypredict question focuses and produce the question. Based on this framework, wefurther use both exemplars and automatically generated templates to improvecontrollability and diversity. Experiments on two newly collected large-scaledatasets show that our model improves question quality over competitivecomparisons based on automatic metrics. Human judges also rate our modeloutputs highly in answerability, coverage of scope, and overall quality.Finally, our model variants with templates can produce questions with enhancedcontrollability and diversity.

Controllable Open-ended Question Generation with A New Question Type Ontology