Search Results for author: Simon Razniewski

Found 28 papers, 7 papers with code

Answering Count Queries with Explanatory Evidence

no code implementations11 Apr 2022 Shrestha Ghosh, Simon Razniewski, Gerhard Weikum

A challenging case in web search and question answering are count queries, such as \textit{"number of songs by John Lennon"}.

Question Answering

Materialized Knowledge Bases from Commonsense Transformers

no code implementations CSRR (ACL) 2022 Tuan-Phong Nguyen, Simon Razniewski

Starting from the COMET methodology by Bosselut et al. (2019), generating commonsense knowledge directly from pre-trained language models has recently received significant attention.

Refined Commonsense Knowledge from Large-Scale Web Contents

1 code implementation30 Nov 2021 Tuan-Phong Nguyen, Simon Razniewski, Julien Romero, Gerhard Weikum

Prior works like ConceptNet, COMET and others compiled large CSK collections, but are restricted in their expressiveness to subject-predicate-object (SPO) triples with simple concepts for S and strings for P and O.

Open Information Extraction

Predicting Document Coverage for Relation Extraction

no code implementations26 Nov 2021 Sneha Singhania, Simon Razniewski, Gerhard Weikum

We employ methods combining features with statistical models like TF-IDF and language models like BERT.

Information Retrieval Relation Extraction

Language Models As or For Knowledge Bases

no code implementations10 Oct 2021 Simon Razniewski, Andrew Yates, Nora Kassner, Gerhard Weikum

Pre-trained language models (LMs) have recently gained attention for their potential as an alternative to (or proxy for) explicit knowledge bases (KBs).

KnowFi: Knowledge Extraction from Long Fictional Texts

no code implementations AKBC 2021 Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum

Knowledge base construction has recently been extended to fictional domains like multi-volume novels and TV/movie series, aiming to support explorative queries for fans and sub-culture studies by humanities researchers.

Relation Extraction

Commonsense Knowledge Base Construction in the Age of Big Data

no code implementations5 May 2021 Simon Razniewski

Compiling commonsense knowledge is traditionally an AI topic approached by manual labor.

Commonsense Knowledge Base Construction

SANDI: Story-and-Images Alignment

no code implementations EACL 2021 Sreyasi Nag Chowdhury, Simon Razniewski, Gerhard Weikum

The Internet contains a multitude of social media posts and other of stories where text is interspersed with images.

Information to Wisdom: Commonsense Knowledge Extraction and Compilation

no code implementations4 Mar 2021 Simon Razniewski, Niket Tandon, Aparna S. Varde

Commonsense knowledge is a foundational cornerstone of artificial intelligence applications.

Advanced Semantics for Commonsense Knowledge Extraction

1 code implementation2 Nov 2020 Tuan-Phong Nguyen, Simon Razniewski, Gerhard Weikum

Commonsense knowledge (CSK) about concepts and their properties is useful for AI applications such as robust chatbots.

Commonsense Knowledge Base Construction

Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases

no code implementations24 Sep 2020 Gerhard Weikum, Luna Dong, Simon Razniewski, Fabian Suchanek

Equipping machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing goal of AI.

Knowledge Graphs Question Answering

Counting Query Answers over a DL-Lite Knowledge Base (extended version)

no code implementations12 May 2020 Diego Calvanese, Julien Corman, Davide Lanti, Simon Razniewski

Counting answers to a query is an operation supported by virtually all database management systems.

CounQER: A System for Discovering and Linking Count Information in Knowledge Bases

1 code implementation7 May 2020 Shrestha Ghosh, Simon Razniewski, Gerhard Weikum

Predicate constraints of general-purpose knowledge bases (KBs) like Wikidata, DBpedia and Freebase are often limited to subproperty, domain and range constraints.

Question Answering

Uncovering Hidden Semantics of Set Information in Knowledge Bases

1 code implementation6 Mar 2020 Shrestha Ghosh, Simon Razniewski, Gerhard Weikum

This paper focuses on set-valued predicates, i. e., the relationship between an entity and a set of entities.

Question Answering

Enriching Knowledge Bases with Interesting Negative Statements

no code implementations AKBC 2020 Hiba Arnaout, Simon Razniewski, Gerhard Weikum

Negative statements would be important to overcome current limitations of question answering, yet due to their potential abundance, any effort towards compiling them needs a tight coupling with ranking.

Question Answering

Joint Reasoning for Multi-Faceted Commonsense Knowledge

1 code implementation AKBC 2020 Yohan Chalier, Simon Razniewski, Gerhard Weikum

Each concept is treated in isolation from other concepts, and the only quantitative measure (or ranking) of properties is a confidence score that the statement is valid.

Negative Statements Considered Useful

no code implementations13 Jan 2020 Hiba Arnaout, Simon Razniewski, Gerhard Weikum, Jeff Z. Pan

Negative statements are useful to overcome limitations of question answering systems that are mainly geared for positive questions; they can also contribute to informative summaries of entities.

Question Answering

Coverage of Information Extraction from Sentences and Paragraphs

no code implementations IJCNLP 2019 Simon Razniewski, Nitisha Jain, Paramita Mirza, Gerhard Weikum

Scalar implicatures are language features that imply the negation of stronger statements, e. g., {``}She was married twice{''} typically implicates that she was not married thrice.

Story-oriented Image Selection and Placement

no code implementations2 Sep 2019 Sreyasi Nag Chowdhury, Simon Razniewski, Gerhard Weikum

Multimodal contents have become commonplace on the Internet today, manifested as news articles, social media posts, and personal or business blog posts.

Combinatorial Optimization Object Recognition

Commonsense Properties from Query Logs and Question Answering Forums

2 code implementations27 May 2019 Julien Romero, Simon Razniewski, Koninika Pal, Jeff Z. Pan, Archit Sakhadeo, Gerhard Weikum

Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications.

Question Answering

TiFi: Taxonomy Induction for Fictional Domains [Extended version]

no code implementations29 Jan 2019 Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention.

Enriching Knowledge Bases with Counting Quantifiers

1 code implementation10 Jul 2018 Paramita Mirza, Simon Razniewski, Fariz Darari, Gerhard Weikum

In a large-scale experiment, we demonstrate the potential for knowledge base enrichment by applying CINEX to 2, 474 frequent relations in Wikidata.

Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties [Extended Version]

no code implementations20 Sep 2017 Simon Razniewski, Vevake Balaraman, Werner Nutt

In this work, we have developed a human-annotated dataset of 350 preference judgments among pairs of knowledge base properties for fixed entities.

Semantic Similarity Semantic Textual Similarity +1

Cardinal Virtues: Extracting Relation Cardinalities from Text

no code implementations ACL 2017 Paramita Mirza, Simon Razniewski, Fariz Darari, Gerhard Weikum

Information extraction (IE) from text has largely focused on relations between individual entities, such as who has won which award.

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