Gerhard Weikum

Neural Relation Extraction for Knowledge Base Enrichment

2019

We study relation extraction for knowledge base (KB) enrichment. Specifically, we aim to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an …

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 …

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 …

Recursive Question Understanding for Complex Question Answering over Heterogeneous Personal Data

2025

Question answering over mixed sources, like text and tables, has been advanced by verbalizing all contents and encoding it with a language model.A prominent case of such heterogeneous data is personal information: user devices log …

YAGO: A Multilingual Knowledge Base from Wikipedia, Wordnet, and Geonames

2016 · Lecture notes in computer science

YAGO is a large knowledge base that is built automatically from Wikipedia, WordNet and GeoNames. The project combines information from Wikipedias in 10 different languages into a coherent whole, thus giving the knowledge a multilingual …

Automated Template Generation for Question Answering over Knowledge Graphs

2017

Templates are an important asset for question answering over knowledge graphs, simplifying the semantic parsing of input utterances and generating structured queries for interpretable answers. State-of-the-art methods rely on hand-crafted templates with limited coverage. This …

ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters

2018 · arXiv (Cornell University)

To bridge the gap between the capabilities of the state-of-the-art in factoid question answering (QA) and what users ask, we need large datasets of real user questions that capture the various question phenomena users are …