Papers by Ian Roberts
Reasoning Over Paths via Knowledge Base Completion (D19-53)
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| Challenge: | Existing methods to predict missing links in knowledge graphs are lacking. |
| Approach: | They propose a method to automatically rank paths between a source and target entity pair using a knowledge base completion model. |
| Outcome: | The proposed method can rank and rank paths in biomedical knowledge graphs with a KBC model. |
European Language Grid: A Joint Platform for the European Language Technology Community (2021.eacl-demos)
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Georg Rehm, Stelios Piperidis, Kalina Bontcheva, Jan Hajic, Victoria Arranz, Andrejs Vasiļjevs, Gerhard Backfried, Jose Manuel Gomez-Perez, Ulrich Germann, Rémi Calizzano, Nils Feldhus, Stefanie Hegele, Florian Kintzel, Katrin Marheinecke, Julian Moreno-Schneider, Dimitris Galanis, Penny Labropoulou, Miltos Deligiannis, Katerina Gkirtzou, Athanasia Kolovou, Dimitris Gkoumas, Leon Voukoutis, Ian Roberts, Jana Hamrlova, Dusan Varis, Lukas Kacena, Khalid Choukri, Valérie Mapelli, Mickaël Rigault, Julija Melnika, Miro Janosik, Katja Prinz, Andres Garcia-Silva, Cristian Berrio, Ondrej Klejch, Steve Renals
| Challenge: | Europe is a multilingual society, in which dozens of languages are spoken. |
| Approach: | They describe the European Language Grid, which is targeted to evolve into the primary platform and marketplace for LT in Europe by providing one umbrella platform for the European LT landscape. |
| Outcome: | The European Language Grid (ELG) will provide access to 1300 services for all European languages as well as thousands of data sets. |
A Browser-based Open Source Assistant for Multimodal Content Verification (2026.eacl-demo)
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Rosanna Milner, Michael Foster, Twin Karmakharm, Olesya Razuvayevskaya, Valentin Porcellini, Denis Teyssou, Ian Roberts, Kalina Bontcheva
| Challenge: | Disinformation and advanced generative AI content pose a significant challenge for journalists and fact-checkers who must rapidly verify digital media. |
| Approach: | They propose to integrate a browser-based tool that automatically extracts content from a suite of backend NLP classifiers and presents actionable credibility signals and AI-generation likelihood in an easy-to-digest format. |
| Outcome: | The Verification Assistant is a browser-based tool that extracts content and routes it to a suite of backend NLP classifiers, presenting actionable credibility signals, AI-generation likelihood, and other verification advice in an easy-to-digest format. |
European Language Grid: An Overview (2020.lrec-1)
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Georg Rehm, Maria Berger, Ela Elsholz, Stefanie Hegele, Florian Kintzel, Katrin Marheinecke, Stelios Piperidis, Miltos Deligiannis, Dimitris Galanis, Katerina Gkirtzou, Penny Labropoulou, Kalina Bontcheva, David Jones, Ian Roberts, Jan Hajič, Jana Hamrlová, Lukáš Kačena, Khalid Choukri, Victoria Arranz, Andrejs Vasiļjevs, Orians Anvari, Andis Lagzdiņš, Jūlija Meļņika, Gerhard Backfried, Erinç Dikici, Miroslav Janosik, Katja Prinz, Christoph Prinz, Severin Stampler, Dorothea Thomas-Aniola, José Manuel Gómez-Pérez, Andres Garcia Silva, Christian Berrío, Ulrich Germann, Steve Renals, Ondrej Klejch
| Challenge: | European LT business is dominated by hundreds of SMEs and a few large players, with technologies that outperform the global players. |
| Approach: | European Language Grid (ELG) project addresses this by establishing the ELG as the primary platform for LT in Europe. |
| Outcome: | European Language Grid (ELG) will be primary platform for LT in Europe . it will provide access to hundreds of commercial and non-commercial LTs for all European languages, including running tools and services as well as data sets and resources. |
Deep Bidirectional Transformers for Relation Extraction without Supervision (D19-61)
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| Challenge: | Existing frameworks for relation extraction use distant supervision instead of annotated data. |
| Approach: | They propose a framework to deal with relation extraction tasks without supervision . they use syntactic parsing and pre-trained word embeddings to extract relations . |
| Outcome: | The proposed framework outperforms baselines on four biomedical datasets and achieves slightly worse results than the state-of-the-art in three out of four data sets. |
GATE Teamware 2: An open-source tool for collaborative document classification annotation (2023.eacl-demo)
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| Challenge: | GATE Teamware 2 is an open-source web-based platform for managing teams of annotators working on document classification tasks. |
| Approach: | They present GATE Teamware 2: an open-source web-based platform for managing teams of annotators working on document classification tasks. |
| Outcome: | GATE Teamware 2 is an open-source web-based platform for managing teams of annotators working on document classification tasks. |
Efficient Annotator Reliability Assessment with EffiARA (2025.acl-demo)
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| Challenge: | Obtaining annotations from experts is ideal, but this expertise is logistically and financially costly. |
| Approach: | They propose an annotation framework that supports the whole annotation pipeline from understanding the resources required for an annotation task to compiling the annotated dataset. |
| Outcome: | The proposed framework improves classification performance through annotator-reliability-based soft-label aggregation and sample weighting, and increases agreement among annotators through removal of identifying and replacing an unreliable annotation. |