94 citations · 134 across the 6 of their papers we have counts for
6 papers
Improving Wikipedia Verifiability with AI
Fabio Petroni, Samuel Broscheit, Aleksandra Piktus +10
Verifiability is a core content policy of Wikipedia: claims that are likely to be challenged need to be backed by citations. There are millions of articles available online and tho…
The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus
Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin +8
In order to address increasing demands of real-world applications, the research for knowledge-intensive NLP (KI-NLP) should advance by capturing the challenges of a truly open-doma…
Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking
Samuel Broscheit
A typical architecture for end-to-end entity linking systems consists of three steps: mention detection, candidate generation and entity disambiguation. In this study we investigat…
OPIEC: An Open Information Extraction Corpus
Kiril Gashteovski, Sebastian Wanner, Sven Hertling +2
Open information extraction (OIE) systems extract relations and their arguments from natural language text in an unsupervised manner. The resulting extractions are a valuable resou…
A Relational Tucker Decomposition for Multi-Relational Link Prediction
Yanjie Wang, Samuel Broscheit, Rainer Gemulla
We propose the Relational Tucker3 (RT) decomposition for multi-relational link prediction in knowledge graphs. We show that many existing knowledge graph embedding models are speci…
On Evaluating Embedding Models for Knowledge Base Completion
Yanjie Wang, Daniel Ruffinelli, Rainer Gemulla +2
Knowledge bases contribute to many web search and mining tasks, yet they are often incomplete. To add missing facts to a given knowledge base, various embedding models have been pr…