1 code implementation • CSRNLP (LREC) 2022 • Aleksandra Gabryszak, Philippe Thomas
In this paper we show how aspect-based sentiment analysis might help public transport companies to improve their social responsibility for accessible travel.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
no code implementations • 17 Aug 2023 • Mohammed Bin Sumait, Aleksandra Gabryszak, Leonhard Hennig, Roland Roller
Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are explicitly not present, possibly present, not mentioned, or affirmed.
1 code implementation • KONVENS (WS) 2021 • Leonhard Hennig, Phuc Tran Truong, Aleksandra Gabryszak
We present MobIE, a German-language dataset, which is human-annotated with 20 coarse- and fine-grained entity types and entity linking information for geographically linkable entities.
3 code implementations • 7 Jul 2020 • Karolina Zaczynska, Nils Feldhus, Robert Schwarzenberg, Aleksandra Gabryszak, Sebastian Möller
Most of the studies were conducted for the English language, however.
1 code implementation • ACL 2020 • Christoph Alt, Aleksandra Gabryszak, Leonhard Hennig
TACRED (Zhang et al., 2017) is one of the largest, most widely used crowdsourced datasets in Relation Extraction (RE).
2 code implementations • ACL 2020 • Christoph Alt, Aleksandra Gabryszak, Leonhard Hennig
Despite the recent progress, little is known about the features captured by state-of-the-art neural relation extraction (RE) models.
no code implementations • LREC 2018 • Saskia Schön, Veselina Mironova, Aleksandra Gabryszak, Leonhard Hennig
Recognizing non-standard entity types and relations, such as B2B products, product classes and their producers, in news and forum texts is important in application areas such as supply chain monitoring and market research.
no code implementations • LREC 2018 • Martin Schiersch, Veselina Mironova, Maximilian Schmitt, Philippe Thomas, Aleksandra Gabryszak, Leonhard Hennig
Monitoring mobility- and industry-relevant events is important in areas such as personal travel planning and supply chain management, but extracting events pertaining to specific companies, transit routes and locations from heterogeneous, high-volume text streams remains a significant challenge.