no code implementations • LREC 2012 • John McCrae, Elena Montiel-Ponsoda, Philipp Cimiano
The creation of language resources is a time-consuming process requiring the efforts of many people.
no code implementations • LREC 2014 • Roman Klinger, Philipp Cimiano
Contributing to this situation, this paper describes the Bielefeld University Sentiment Analysis Corpus for German and English (USAGE), which we offer freely to the community and which contains the annotation of product reviews from Amazon with both aspects and subjective phrases.
no code implementations • LREC 2014 • Maud Ehrmann, Francesco Cecconi, Daniele Vannella, John Philip McCrae, Philipp Cimiano, Roberto Navigli
Recent years have witnessed a surge in the amount of semantic information published on the Web.
no code implementations • WS 2014 • Benjamin Paassen, Andreas St{\"o}ckel, Raphael Dickfelder, Jan Philip G{\"o}pfert, Nicole Brazda, Tarek Kirchhoffer, Hans Werner M{\"u}ller, Roman Klinger, Matthias Hartung, Philipp Cimiano
no code implementations • LREC 2016 • John Philip McCrae, Christian Chiarcos, Francis Bond, Philipp Cimiano, Thierry Declerck, Gerard de Melo, Jorge Gracia, Sebastian Hellmann, Bettina Klimek, Steven Moran, Petya Osenova, Antonio Pareja-Lora, Jonathan Pool
The Open Linguistics Working Group (OWLG) brings together researchers from various fields of linguistics, natural language processing, and information technology to present and discuss principles, case studies, and best practices for representing, publishing and linking linguistic data collections.
no code implementations • LREC 2016 • Patrick Holthaus, Christian Leichsenring, Jasmin Bernotat, Viktor Richter, Marian Pohling, Birte Carlmeyer, Norman K{\"o}ster, Sebastian Meyer zu Borgsen, Ren{\'e} Zorn, Birte Schiffhauer, Kai Frederic Engelmann, Florian Lier, Simon Schulz, Philipp Cimiano, Friederike Eyssel, Thomas Hermann, Franz Kummert, David Schlangen, Sven Wachsmuth, Petra Wagner, Britta Wrede, Sebastian Wrede
In order to explore intuitive verbal and non-verbal interfaces in smart environments we recorded user interactions with an intelligent apartment.
no code implementations • LREC 2016 • Bettina Lanser, Christina Unger, Philipp Cimiano
In order to make the growing amount of conceptual knowledge available through ontologies and datasets accessible to humans, NLP applications need access to information on how this knowledge can be verbalized in natural language.
no code implementations • 21 Jul 2016 • Janik Jaskolski, Fabian Siegberg, Thomas Tibroni, Philipp Cimiano, Roman Klinger
The popularity of distance education programs is increasing at a fast pace.
no code implementations • EACL 2017 • Matthias Hartung, Fabian Kaupmann, Soufian Jebbara, Philipp Cimiano
Word embeddings have been shown to be highly effective in a variety of lexical semantic tasks.
no code implementations • 19 Sep 2017 • Soufian Jebbara, Philipp Cimiano
We propose a neural network based system to address the task of Aspect-Based Sentiment Analysis to compete in Task 2 of the ESWC-2016 Challenge on Semantic Sentiment Analysis.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3
1 code implementation • 19 Sep 2017 • Soufian Jebbara, Philipp Cimiano
We present a novel neural architecture for sentiment analysis as a relation extraction problem that addresses this problem by dividing it into three subtasks: i) identification of aspect and opinion terms, ii) labeling of opinion terms with a sentiment, and iii) extraction of relations between opinion terms and aspect terms.
no code implementations • WS 2017 • Soufian Jebbara, Philipp Cimiano
In this work, we investigate whether character-level models can improve the performance for the identification of opinion target expressions.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • 26 Sep 2017 • Hendrik ter Horst, Matthias Hartung, Roman Klinger, Matthias Zwick, Philipp Cimiano
In the context of personalized medicine, text mining methods pose an interesting option for identifying disease-gene associations, as they can be used to generate novel links between diseases and genes which may complement knowledge from structured databases.
1 code implementation • 26 Feb 2018 • Sherzod Hakimov, Soufian Jebbara, Philipp Cimiano
We present the first multilingual QALD pipeline that induces a model from training data for mapping a natural language question into logical form as probabilistic inference.
no code implementations • ACL 2018 • Matthias Hartung, Hendrik ter Horst, Frank Grimm, Tim Diekmann, Roman Klinger, Philipp Cimiano
Supervised machine learning algorithms require training data whose generation for complex relation extraction tasks tends to be difficult.
1 code implementation • COLING 2018 • Matthias Orlikowski, Matthias Hartung, Philipp Cimiano
We show that a model which treats the concept terms as analogous and learns weights to compensate for diachronic changes (weighted linear combination) is able to more accurately predict the missing term than a learned transformation and two baselines for most of the evaluated concepts.
no code implementations • 6 Dec 2018 • Sherzod Hakimov, Soufian Jebbara, Philipp Cimiano
We address the task of answering simple questions, consisting in predicting the subject and predicate of a triple given a question.
no code implementations • NAACL 2019 • Soufian Jebbara, Philipp Cimiano
In this work, we address the lack of available annotated data for specific languages by proposing a zero-shot cross-lingual approach for the extraction of opinion target expressions.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • LREC 2020 • Thierry Declerck, John Philip McCrae, Matthias Hartung, Jorge Gracia, Christian Chiarcos, Elena Montiel-Ponsoda, Philipp Cimiano, Artem Revenko, Roser Saur{\'\i}, Deirdre Lee, Stefania Racioppa, Jamal Abdul Nasir, Matthias Orlikowsk, Marta Lanau-Coronas, Christian F{\"a}th, Mariano Rico, Mohammad Fazleh Elahi, Maria Khvalchik, Meritxell Gonzalez, Katharine Cooney
In this paper we describe the contributions made by the European H2020 project {``}Pr{\^e}t-{\`a}-LLOD{''} ({`}Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors{'}) to the further development of the Linguistic Linked Open Data (LLOD) infrastructure.
no code implementations • LREC 2020 • Maria Pia di Buono, Philipp Cimiano, Mohammad Fazleh Elahi, Frank Grimm
While we apply this paradigm to the transformation and hosting of terminologies as linked data, the paradigm can be applied to any other resource format as well.
no code implementations • Joint Conference on Lexical and Computational Semantics 2021 • Frank Grimm, Philipp Cimiano
Recent question answering and machine reading benchmarks frequently reduce the task to one of pinpointing spans within a certain text passage that answers the given question.
1 code implementation • EMNLP (ArgMining) 2021 • Milad Alshomary, Timon Gurcke, Shahbaz Syed, Philipp Heinrich, Maximilian Spliethöver, Philipp Cimiano, Martin Potthast, Henning Wachsmuth
Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments.
1 code implementation • 15 May 2023 • Moritz Plenz, Juri Opitz, Philipp Heinisch, Philipp Cimiano, Anette Frank
Arguments often do not make explicit how a conclusion follows from its premises.
1 code implementation • 20 Jun 2023 • Matthias Orlikowski, Paul Röttger, Philipp Cimiano, Dirk Hovy
To account for sociodemographics in models of individual annotator behaviour, we introduce group-specific layers to multi-annotator models.
no code implementations • 22 Sep 2023 • Moritz Blum, Basil Ell, Philipp Cimiano
Furthermore, we find that because OTTR templates encapsulate modeling decisions, the engineering process becomes flexible, meaning that design decisions can be changed at little cost.
1 code implementation • 6 Nov 2023 • Philipp Heinisch, Matthias Orlikowski, Julia Romberg, Philipp Cimiano
To best represent the interplay of individual and shared perspectives, we consider a continuum of approaches ranging from models that fully aggregate perspectives into a majority label to "share nothing"-architectures in which each annotator is considered in isolation from all other annotators.
no code implementations • 29 Feb 2024 • Gennaro Nolano, Moritz Blum, Basil Ell, Philipp Cimiano
For instance, in the context of relation extraction (RE), we would expect a model to identify the same relation independently of the entities involved in it.
no code implementations • 1 Mar 2024 • Milad Alshomary, Felix Lange, Meisam Booshehri, Meghdut Sengupta, Philipp Cimiano, Henning Wachsmuth
In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee's side.
no code implementations • EMNLP (NLP+CSS) 2020 • Angelika Maier, Philipp Cimiano
To support this task, we present an approach that extracts indications of independence on different life aspects from the day-to-day documentation that social workers create.
1 code implementation • ArgMining (ACL) 2022 • Philipp Heinisch, Anette Frank, Juri Opitz, Moritz Plenz, Philipp Cimiano
This paper provides an overview of the Argument Validity and Novelty Prediction Shared Task that was organized as part of the 9th Workshop on Argument Mining (ArgMining 2022).
Ranked #1 on ValNov on ValNov Subtask A
no code implementations • ArgMining (ACL) 2022 • Philipp Heinisch, Moritz Plenz, Juri Opitz, Anette Frank, Philipp Cimiano
Using only training data retrieved from related datasets by automatically labeling them for validity and novelty, combined with synthetic data, outperforms the baseline by 11. 5 points in F_1-score.
no code implementations • BioNLP (ACL) 2022 • Christian Witte, Philipp Cimiano
We present a deep learning based information extraction system that can extract the design and results of a published abstract describing a Randomized Controlled Trial (RCT).
no code implementations • EMNLP (spnlp) 2020 • Hendrik ter Horst, Philipp Cimiano
We show that cardinality prediction can successfully be approached by modeling the overall task as a joint inference problem, predicting the number of individuals of certain classes while at the same time extracting their properties.
1 code implementation • EMNLP (ArgMining) 2021 • Juri Opitz, Philipp Heinisch, Philipp Wiesenbach, Philipp Cimiano, Anette Frank
When assessing the similarity of arguments, researchers typically use approaches that do not provide interpretable evidence or justifications for their ratings.