Ruprecht-Karls-Universität Heidelberg

Chair of Computational Linguistics

Prof. Dr. Anette Frank

Anette Frank

Contact

Institut für Computerlinguistik        email: frank sign cl sign uni-heidelberg sign de
Im Neuenheimer Feld 325phone: +49-(0)6221/54-3247
D-69120 Heidelberg sek: +49-(0)6221/54-3245
Germany fax: +49-(0)6221/54-3242

Research

My research focuses on statistical - nowadays mostly neural - NLP methods for discourse-oriented semantic analysis and information access tasks with the aim of improving computational natural language understanding.

For more information please consult my research and publication pages and the pages of my research group.

I am member of the standing reviewer committee of TACL and member of the Editorial Board of the Computational Linguistics Journal (2018 -- 2021).

Office Hours and Teaching

News

Three members of the NLP group will attend EurNLP 2019 in London to present and discuss their research:

  • 
Todor Mihaylov: Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension
  • Letitia Parcalabescu: Unsupervised Text to Scene Graph Alignment with WordNet Neighborhood
  • Debjit Paul: Graph-based Multi-Hop Commonsense Knowledge

Selected new publications

DFG accepts new project on Knowledge-based Argumentation Analysis

The new project ExpLAIN: Between the lines -- Knowledge-based Analysis of Argumentation in a formal Argumentation Inference System is funded within the DFG priority program RATIO: Robust Argumentation Machines.

The project is jointly conducted by Prof. Anette Frank and Prof. Heiner Stuckenschmidt (University of Mannheim) and their associated research groups.

The project aims to

  • uncover missing explanatory links in argumentative texts,
  • fill in automatically acquired knowledge that makes the structure of the argument explicit, and
  • will establish and verify the knowledge-enhanced argumentation structure with a combination of formal reasoning and machine learning.

Within the priority programme RATIO: Robust Argumentation Machines we will contribute to community actions, shared tasks and evaluation efforts.

Current Projects

Completed Projects

Former Affiliations

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