The paper “HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings” by Saba Anwar, Dmitry Ustalov, Nikolay Arefyev, Chris Biemann, Simone Paolo Ponzetto, and Alexander Panchenko has been accepted for publication at SemEval 2019.
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (QasemiZadeh et al., 2019). Our approach separates this task into two independent steps: verb clustering using word and their context embeddings and role labeling by combining these embeddings with syntactical features. A simple combination of these steps shows very competitive results and can be extended to process other datasets and languages.
HHMM is an abbreviation for Hansestadt Hamburg, Mannheim, and Moscow. It is chosen to avoid confusion with hidden Markov models.
The article “Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction” by Dmitry Ustalov, Alexander Panchenko, Chris Biemann, and Simone Paolo Ponzetto has been accepted for publication at the Computational Linguistics (CL) journal by MIT Press.
We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of domains. This algorithm creates an intermediate representation of the input graph that reflects the “ambiguity” of its nodes. It uses hard clustering to discover clusters in this “disambiguated” intermediate graph. After outlining the approach and analyzing its computational complexity, we demonstrate that Watset shows competitive results in three applications: unsupervised synset induction from a synonymy graph, unsupervised semantic frame induction from dependency triples, and unsupervised semantic class induction from a distributional thesaurus. Our algorithm is generic and can be also applied to other networks of linguistic data.
Prof. Graeme Hirst from the University of Toronto is visiting the DWS Group during March. Graeme is well known for his work on natural language processing. He will work with PhD students from the AI and the NLP Area on advanced methods for argumentation analysis in natural language texts. For more information about Graeme and his work visit: www.cs.toronto.edu/~gh/
We are happy to announce that the Deutsche Forschungsgemeinschaft accepted our proposal for extending a joint research project on hybrid semantic representations together with our friends and colleagues of the Language Technology Group of the University of Hamburg.
The project, titled „Joining graph- and vector-based sense representations for semantic end-user information access“ (JOIN-T 2) builds upon and aims at bringing our JOIN-T project (also funded funded by DFG) one step forward. Our vision for the next three years is to explore ways to produce semantic representations that combine the interpretability of manually crafted resources and sparse representations with the accuracy and high coverage of dense neural embeddings.
Stay tuned for forthcoming research papers and resources!
Our long paper submission
„Investigating the Role of Argumentation in the Rhetorical Analysis of Scientific Publications with Neural Multi-Task Learning Models " (Anne Lauscher, Goran Glavaš, Kai Eckert, and Simone Paolo Ponzetto)
got accepted at the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), one of the top-tier conferences in natural language processing!
The position paper „Automatic Assessment of Conceptual Text Complexity Using Knowledge Graphs“ by Sanja Štajner and Ioana Hulpus has been accepted at the 27th International Conference on Computational Linguistics (COLING 2018), the premier international conference on Computational Linguistics.
Our paper „Entity-Aspect Linking: Providing Fine-Grained Semantics of Entities in Context“ has recently won the Vannevar Bush best paper award at the 2018 Joint Conference on Digital Libraries (JCDL), the top conference in the field of digital libraries!
The work, coauthored by Federico Nanni, Simone Paolo Ponzetto and Laura Dietz, is part of a collaboration between the DWS group and the University of New Hampshire in the context of an Elite Post-Doc grant of the Baden-Württemberg Stiftung recently awarded from Laura.
Congratulations also to Myriam Traub, Thaer Samar, Jacco van Ossenbruggen and Lynda Hardman, who, with their work, share with us the 2018 best paper award!
We have three papers to be presented at the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), the premier international conference on Computational Linguistics and Natural Language Processing.
Two short papers prepared in collaboration with our colleagues from the University of Cambridge, the University of Hamburg and the University of Oslo have been accepted at the main conference track:
Goran Glavaš, Ivan Vulić: Explicit Retrofitting of Distributional Word Vectors. Dmitry Ustalov, Alexander Panchenko, Andrei Kutuzov, Chris Biemann, Simone Paolo Ponzetto: Unsupervised Semantic Frame Induction using Triclustering.
One paper has been accepted at the 3rd Workshop on Representation Learning for NLP (RepL4NLP) hosted by ACL 2018:
Samuel Broscheit: Learning Distributional Token Representations from Visual Features.
Lydia Weiland has successfully defended her PhD thesis on „Understanding the Message of Images“ today.