Seminar — Feiyu Xu & Prof. Hans Uszkoreit
Speaker: | Feiyu Xu & Prof. Hans Uszkoreit, Language Technology Lab, Deutsches Forschungszentrum für Künstliche Intelligenz & Department of Computational Linguistics,Saarland University |
Title: | Minimally Supervised Learning of Relation Extraction Rules using Semantic Seeds |
Date: | 11am, 21 May 2007 |
Location: | MIB, Room: 2.048 |
Abstract: | We will present a new minimally supervised machine learning
framework for extracting relations of various complexity. Bootstrapping
starts from a small set of n-ary relation instances as "seeds" in order
to automatically learn pattern rules from parsed data, which then can
extract new instances of the relation and its projections. We propose a
novel rule representation model that enables the composition of n-ary
relation rules on top of the rules for projections of the relation. The
compositional approach to rule construction is supported by a bottom-up
pattern extraction method working on dependency structures. In
comparison to other automatic approaches, our rules cannot only localize
relation arguments but also assign their exact target argument roles.
The evaluation results compare favorably with those of existing pattern
acquisition approaches in both recall and precision. For one extraction
task a single seed event suffices to get patterns that find most of the
relevant events. For another task we need larger number of seed events |
Presentation [PowerPoint]
Featured News
- FinNLP-FNP-LLMFinLegal @ COLING-2025 - Call for papers
- Keynote talk at Manchester Law and Technology Conference
- Keynote talk at ACM Summer School on Data Science, Athens
- Congratulations to PhD student Panagiotis Georgiades
Other News & Events
- Invited talk at the 8th Annual Women in Data Science Event at the American University of Beirut
- Invited talk at the 2nd Symposium on NLP for Social Good (NSG), University of Liverpool
- Invited talk at Annual Meeting of the Danish Society of Occupational and Environmental Medicine
- Advances in Data Science and Artificial Intelligence Conference 2024
- New review article on emotion detection for misinformation