no code implementations • EMNLP 2021 • Harsh Gupta, Luciano del Corro, Samuel Broscheit, Johannes Hoffart, Eliot Brenner
We investigate post-OCR correction in a setting where we have access to different OCR views of the same document.
1 code implementation • 6 Jan 2025 • Tassilo Klein, Clemens Biehl, Margarida Costa, Andre Sres, Jonas Kolk, Johannes Hoffart
Foundation models, particularly those that incorporate Transformer architectures, have demonstrated exceptional performance in domains such as natural language processing and image processing.
1 code implementation • 17 Oct 2024 • Marco Spinaci, Marek Polewczyk, Johannes Hoffart, Markus C. Kohler, Sam Thelin, Tassilo Klein
Self-supervised learning on tabular data seeks to apply advances from natural language and image domains to the diverse domain of tables.
no code implementations • 2 Sep 2023 • Timotheus Kampik, Christian Warmuth, Adrian Rebmann, Ron Agam, Lukas N. P. Egger, Andreas Gerber, Johannes Hoffart, Jonas Kolk, Philipp Herzig, Gero Decker, Han van der Aa, Artem Polyvyanyy, Stefanie Rinderle-Ma, Ingo Weber, Matthias Weidlich
The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a proof-point of the challenges that purely statistics-based approaches have in terms of safety and trustworthiness.
1 code implementation • 30 Jan 2023 • Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Johannes Hoffart, Toyotaro Suzumura, Manish Singh
$\mathcal{KP}$ addresses this by representing the topology of the KG completion methods through the lens of topological data analysis, concretely using persistent homology.
1 code implementation • 12 Aug 2021 • Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Saeedeh Shekarpour, Isaiah Onando Mulang, Johannes Hoffart
A few KGE techniques address interpretability, i. e., mapping the connectivity patterns of the relations (i. e., symmetric/asymmetric, inverse, and composition) to a geometric interpretation such as rotations.
1 code implementation • Findings (ACL) 2021 • Abhishek Nadgeri, Anson Bastos, Kuldeep Singh, Isaiah Onando Mulang', Johannes Hoffart, Saeedeh Shekarpour, Vijay Saraswat
We present a novel method for relation extraction (RE) from a single sentence, mapping the sentence and two given entities to a canonical fact in a knowledge graph (KG).
1 code implementation • EACL 2021 • Manoj Prabhakar Kannan Ravi, Kuldeep Singh, Isaiah Onando Mulang', Saeedeh Shekarpour, Johannes Hoffart, Jens Lehmann
Our empirical study was conducted on two well-known knowledge bases (i. e., Wikidata and Wikipedia).
Ranked #1 on
Entity Linking
on MSNBC
1 code implementation • 18 Sep 2020 • Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Isaiah Onando Mulang', Saeedeh Shekarpour, Johannes Hoffart, Manohar Kaul
In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG).
1 code implementation • 12 Aug 2020 • Isaiah Onando Mulang', Kuldeep Singh, Chaitali Prabhu, Abhishek Nadgeri, Johannes Hoffart, Jens Lehmann
We further hypothesize that our proposed KG context can be standardized for Wikipedia, and we evaluate the impact of KG context on state-of-the-art NED model for the Wikipedia knowledge base.
Ranked #2 on
Entity Disambiguation
on AIDA-CoNLL
no code implementations • EMNLP (ECONLP) 2021 • Luciano Del Corro, Johannes Hoffart
We present a method to automatically identify financially relevant news using stock price movements and news headlines as input.
no code implementations • ACL 2018 • Prabal Agarwal, Jannik Str{\"o}tgen, Luciano del Corro, Johannes Hoffart, Gerhard Weikum
Named Entity Disambiguation (NED) systems perform well on news articles and other texts covering a specific time interval.
no code implementations • ACL 2018 • Dominic Seyler, Tatiana Dembelova, Luciano del Corro, Johannes Hoffart, Gerhard Weikum
In this work, we discuss the importance of external knowledge for performing Named Entity Recognition (NER).
no code implementations • 11 Sep 2017 • Dominic Seyler, Tatiana Dembelova, Luciano del Corro, Johannes Hoffart, Gerhard Weikum
KnowNER is a multilingual Named Entity Recognition (NER) system that leverages different degrees of external knowledge.
Multilingual Named Entity Recognition
named-entity-recognition
+2
no code implementations • 1 Jul 2011 • Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, Gerhard Weikum
Disambiguating named entities in naturallanguage text maps mentions of ambiguous names onto canonical entities like people or places, registered in a knowledge base such as DBpedia or YAGO.
Ranked #17 on
Entity Linking
on AIDA-CoNLL