Simon Razniewski

Predicting Document Coverage for Relation Extraction

2021 · arXiv (Cornell University)

This paper presents a new task of predicting the coverage of a text document for relation extraction (RE): does the document contain many relational tuples for a given entity? Coverage predictions are useful in selecting …

Do Children Texts Hold The Key To Commonsense Knowledge?

2022

Compiling comprehensive repositories of commonsense knowledge is a long-standing problem in AI. Many concerns revolve around the issue of reporting bias, i.e., that frequency in text sources is not a good proxy for relevance or …

Can large language models generate salient negative statements?

2023 · arXiv (Cornell University)

We examine the ability of large language models (LLMs) to generate salient (interesting) negative statements about real-world entities; an emerging research topic of the last few years. We probe the LLMs using zero- and k-shot …

Knowledge Base Completion for Long-Tail Entities

2023 · arXiv (Cornell University)

Despite their impressive scale, knowledge bases (KBs), such as Wikidata, still contain significant gaps. Language models (LMs) have been proposed as a source for filling these gaps. However, prior works have focused on prominent entities …