We present a neural model for question generation from knowledge base triples in a "Zero-Shot" setup, that is generating questions for triples containing predicates, subject types or object types that were not seen at training time.
Ranked #14 on Zero-shot Text Search on BEIR
We explore methods to extract relations between named entities from free text in an unsupervised setting.
Relation Discovery discovers predicates (relation types) from a text corpus relying on the co-occurrence of two named entities in the same sentence.
We explore the problem of generating natural language summaries for Semantic Web data.