Our latest publications - LTG

• Hassan, Syed Zohaib; Salehi, Pegah; Røed, Ragnhild Klingenberg; Halvorsen, Pål; Baugerud, Gunn Astrid & Johnson, Miriam Sinkerud [Show all 11 contributors for this article] (2022). Towards an AI-driven talking avatar in virtual reality for investigative interviews of children . In Claypool, Mark & Eg, Ragnhild (Ed.), Proceedings of the 2nd Workshop on Games Systems - ACM Multimedia Systems Conference. Association for Computing Machinery (ACM). ISSN 978-1-4503-9381-2. p. 9–15. doi: https%3A/doi.org/10.1145/3534085.3534340.
• Pilán, Ildikó; Lison, Pierre; Øvrelid, Lilja; Papadopoulou, Anthi; Sánchez, David & Batet, Montserrat (2022). The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization. Computational Linguistics. ISSN 0891-2017. doi: 10.1162/coli_a_00458.
• Papadopoulou, Anthi; Yu, Yunhao; Lison, Pierre & Øvrelid, Lilja (2022). Neural Text Sanitization with Explicit Measures of Privacy Risk, The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-955917-65-0. p. 271–229.
• Mæhlum, Petter; Haug, Dag Trygve Truslew; Jørgensen, Tollef Emil; Kåsen, Andre; Nøklestad, Anders & Rønningstad, Egil [Show all 9 contributors for this article] (2022). NARC – Norwegian Anaphora Resolution Corpus. Proceedings of the 29th International Conference on Computational Linguistics. ISSN 2951-2093.
• Rønningstad, Egil; Øvrelid, Lilja & Velldal, Erik (2022). Entity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey. Proceedings of the 29th International Conference on Computational Linguistics. ISSN 2951-2093. p. 6773–6783. Full text in Research Archive Show summary

  This paper explores the task of identifying the overall sentiment expressed towards volitional entities (persons and organizations) in a document - what we refer to as Entity-Level Sentiment Analysis (ELSA). While identifying sentiment conveyed towards an entity is well researched for shorter texts like tweets, we find little to no research on this specific task for longer texts with multiple mentions and opinions towards the same entity. This lack of research would be understandable if ELSA can be derived from existing tasks and models. To assess this, we annotate a set of professional reviews for their overall sentiment towards each volitional entity in the text. We sample from data already annotated for document-level, sentence-level, and target-level sentiment in a multi-domain review corpus, and our results indicate that there is no single proxy task that provides this overall sentiment we seek for the entities at a satisfactory level of performance. We present a suite of experiments aiming to assess the contribution towards ELSA provided by document-, sentence-, and target-level sentiment analysis, and provide a discussion of their shortcomings. We show that sentiment in our dataset is expressed not only with an entity mention as target, but also towards targets with a sentiment-relevant relation to a volitional entity. In our data, these relations extend beyond anaphoric coreference resolution, and our findings call for further research of the topic. Finally, we also present a survey of previous relevant work.

• Wold, Sondre (2022). The Effectiveness of Masked Language Modeling and Adapters for Factual Knowledge Injection, Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-955917-22-3.
• Touileb, Samia; Lilja, Øvrelid & Erik, Velldal (2022). Occupational Biases in Norwegian and Multilingual Language Models. In Christine, Basta; Marta R., Costa-jussà; Hila, Gonen; Christian, Hardmeier & Gabriel, Stanovsky (Ed.), Proceedings of The 4th Workshop on Gender Bias in Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-955917-68-1. p. 200–211. doi: 10.18653/v1/2022.gebnlp-1.21.
• Aksenova, Anna; Gavrishina, Ekaterina; Rykov, Elisei & Kutuzov, Andrei (2022). RuDSI: Graph-based Word Sense Induction Dataset for Russian, Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-955917-22-3. p. 77–88.
• Kutuzov, Andrei; Velldal, Erik & Øvrelid, Lilja (2022). Contextualized embeddings for semantic change detection: Lessons learned . Northern European Journal of Language Technology (NEJLT). ISSN 2000-1533. 8(1). doi: 10.3384/nejlt.2000-1533.2022.3478.
• Buljan, Maja; Nivre, Joakim; Oepen, Stephan & Øvrelid, Lilja (2022). A tale of four parsers: methodological reflections on diagnostic evaluation and in-depth error analysis for meaning representation parsing. Language Resources and Evaluation. ISSN 1574-020X. p. 1–28. doi: 10.1007/s10579-022-09591-7.
• Barnes, Jeremy; Oberlaender, Laura; Troiano, Enrica; Kutuzov, Andrei; Buchmann, Jan & Agerri, Rodrigo [Show all 8 contributors for this article] (2022). SemEval 2022 Task 10: Structured Sentiment Analysis. In Emerson, Guy; Schluter, Natalie; Stanovsky, Gabriel; Kumar, Ritesh; Palmer, Alexis; Schneider, Nathan; Singh, Siddarth & Ratan, Shyam (Ed.), Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Association for Computational Linguistics. ISSN 978-1-955917-80-3.
• Papadopoulou, Anthi; Lison, Pierre; Øvrelid, Lilja & Pilán, Ildikó (2022). Bootstrapping Text Anonymization Models with Distant Supervision. In Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Odijk, Jan & Piperidis, Stelios (Ed.), Proceedings of the 13th Language Resources and Evaluation Conference. European Language Resources Association. ISSN 979-10-95546-72-6. p. 4477–4487.
• Kutuzov, Andrei; Touileb, Samia; Mæhlum, Petter; Enstad, Tita & Wittemann, Alexandra (2022). NorDiaChange: Diachronic Semantic Change Dataset for Norwegian, Proceedings of the Language Resources and Evaluation Conference. European Language Resources Association. ISSN 979-10-95546-72-6. p. 2563–2572.
• Samuel, David; Barnes, Jeremy; Kurtz, Robin; Oepen, Stephan; Øvrelid, Lilja & Velldal, Erik (2022). Direct parsing to sentiment graphs. Association for Computational Linguistics (ACL). Annual Meeting Conference Proceedings. ISSN 0736-587X. 2(60), p. 470–478. doi: 10.18653/v1/2022.acl-short.51.
• Giulianelli, Mario; Kutuzov, Andrei & Pivovarova, Lidia (2022). Do Not Fire the Linguist: Grammatical Profiles Help Language Models Detect Semantic Change, Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change. Association for Computational Linguistics. ISSN 978-1-955917-42-1. p. 54–67.
• Ravishankar, Vinit & Søgaard, Anders (2021). The Impact of Positional Encodings on Multilingual Compression, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-955917-09-4. p. 763–777. doi: 10.18653/v1/2021.emnlp-main.59.
• Ravishankar, Vinit; Kulmizev, Artur; Abdou, Mostafa; Søgaard, Anders & Nivre, Joakim (2021). Attention Can Reflect Syntactic Structure (If You Let It). In Merlo, Paola; Tiedemann, Jörg & Tsarfaty, Reut (Ed.), Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-954085-02-2. p. 3031–3045. doi: 10.18653/v1/2021.eacl-main.264.
• Trattner, Christoph; Jannach, Dietmar; Motta, Enrico; Meijer, Irene Costera; Diakopoulos, Nicholas & Elahi, Mehdi [Show all 13 contributors for this article] (2021). Responsible media technology and AI: challenges and research directions. AI and Ethics. ISSN 2730-5953. doi: 10.1007/s43681-021-00126-4. Full text in Research Archive
• Laake, Signe & Øvrelid, Lilja (2021). Forskjeller mellom talemål og skriftspråk: Hva kan trebanker fortelle oss? In Hagen, Kristin; Kristoffersen, Gjert; Vangsnes, Øystein Alexander & Åfarli, Tor Anders (Ed.), Språk i arkiva. Ny forsking om eldre talemål frå LIA-prosjektet . Novus Forlag. ISSN 9788283900811. p. 65–86.
• Yeghaneh Abkenar, Mohammad; Stede, Manfred & Oepen, Stephan (2021). Neural Argumentation Mining on Essays and Microtexts with Contextualized Word Embeddings. CEUR Workshop Proceedings. ISSN 1613-0073. 2957.
• Kutuzov, Andrei; Giulianelli, Mario & Pivovarova, Lidia (2021). Grammatical Profiling for Semantic Change Detection, Proceedings of the 25th Conference on Computational Natural Language Learning. Association for Computational Linguistics. ISSN 978-1-955917-05-6. p. 423–434.
• Moore, Andrew & Barnes, Jeremy Claude (2021). Multi-task Learning of Negation and Speculation for Targeted Sentiment Classification, Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics. ISSN 978-1-954085-46-6. p. 2838–2869.
• Lison, Pierre; Barnes, Jeremy & Hubin, Aliaksandr (2021). skweak: Weak Supervision Made Easy for NLP. In Ji, Heng & Park, Jong (Ed.), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations. Association for Computational Linguistics. ISSN 978-1-954085-56-5. p. 337–346. doi: 10.18653/v1/2021.acl-demo.40. Full text in Research Archive
• Touileb, Samia; Øvrelid, Lilja & Velldal, Erik (2021). Using Gender- and Polarity-Informed Models to Investigate Bias. In Costa-jussà, Marta R.; Gonen, Hila; Hardmeier, Christian & Webster, Kellie (Ed.), Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-954085-61-9. p. 66–74. doi: 10.18653/v1/2021.gebnlp-1.8.
• Touileb, Samia & Barnes, Jeremy (2021). The interplay between language similarity and script on a novel multi-layer Algerian dialect corpus. In Zong, Chengqing; Xia, Fei; Li, Wenjie & Navigli, Roberto (Ed.), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics. ISSN 978-1-954085-54-1. p. 3700–3712. doi: 10.18653/v1/2021.findings-acl.324.
• Iazykova, Tatyana; Kapelyushnik, Denis; Bystrova, Olga & Kutuzov, Andrei (2021). Unreasonable Effectiveness of Rule-Based Heuristics in Solving Russian SuperGLUE Tasks. Komp'yuternaya Lingvistika i Intellektual'nye Tekhnologii. ISSN 2221-7932. 20, p. 302–318. doi: 10.28995/2075-7182-2021-20-302-317.
• Kutuzov, Andrei & Pivovarova, Lidia (2021). Three-part diachronic semantic change dataset for Russian, Proceedings of the 2nd International Workshop on Computational Approaches to Historical Language Change. Association for Computational Linguistics. ISSN 978-1-954085-60-2. p. 7–13.
• Lison, Pierre; Pilán, Ildikó; Sánchez, David; Batet, Montserrat & Øvrelid, Lilja (2021). Anonymisation Models for Text Data: State of the art, Challenges and Future Directions. In Zong, Chengqing; Xia, Fei; Li, Wenjie & Navigli, Roberto (Ed.), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics. ISSN 978-1-954085-52-7. p. 4188–4203. doi: 10.18653/v1/2021.acl-long.323.
• Barnes, Jeremy; Kurtz, Robin; Oepen, Stephan; Øvrelid, Lilja & Velldal, Erik (2021). Structured Sentiment Analysis as Dependency Graph Parsing. In Zong, Chengqing; Xia, Fei; Li, Wenjie & Navigli, Roberto (Ed.), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics. ISSN 978-1-954085-52-7. p. 3387–3402. doi: http%3A/dx.doi.org/10.18653/v1/2021.acl-long.263.
• Garbulowski, Mateusz; Diamanti, Klev; Smolińska, Karolina; Baltzer, Nicholas; Stoll, Patricia & Bornelöv, Susanne [Show all 9 contributors for this article] (2021). R.ROSETTA: an interpretable machine learning framework. BMC Bioinformatics. ISSN 1471-2105. 22(1), p. 1–18. doi: 10.1186/s12859-021-04049-z.
• Barnes, Jeremy; Mæhlum, Petter & Touileb, Samia (2021). NorDial: A Preliminary Corpus of Written Norwegian Dialect Use. In Dobnik, Simon & Øvrelid, Lilja (Ed.), Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7929-614-8. p. 445–451.
• Barnes, Jeremy; Øvrelid, Lilja & Velldal, Erik (2021). If you've got it, flaunt it: Making the most of fine-grained sentiment annotations. In Merlo, Paola; Tiedemann, Jörg & Tsarfaty, Reut (Ed.), Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-954085-02-2. p. 49–62.
• Ravishankar, Vinit; Kutuzov, Andrei; Øvrelid, Lilja & Velldal, Erik (2021). Multilingual ELMo and the Effects of Corpus Sampling. In Dobnik, Simon & Øvrelid, Lilja (Ed.), Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7929-614-8. p. 378–383.
• Mæhlum, Petter; Barnes, Jeremy; Kurtz, Robin; Øvrelid, Lilja & Velldal, Erik (2021). Negation in Norwegian: an annotated dataset . In Dobnik, Simon & Øvrelid, Lilja (Ed.), Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7929-614-8. p. 299–308.
• Kutuzov, Andrei; Barnes, Jeremy; Velldal, Erik; Øvrelid, Lilja & Oepen, Stephan (2021). Large-Scale Contextualised Language Modelling for Norwegian. In Dobnik, Simon & Øvrelid, Lilja (Ed.), Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7929-614-8. p. 30–40.
• Rodina, Julia; Trofimova, Yuliya; Kutuzov, Andrei & Artemova, Ekaterina (2021). ELMo and BERT in Semantic Change Detection for Russian, Proceedings of AIST 2020: Analysis of Images, Social Networks and Texts. Springer. ISSN 978-3-030-72610-2. p. 175–186.
• Kutuzov, Andrei & Kuzmenko, Elizaveta (2021). Representing ELMo embeddings as two-dimensional text online, Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations. Association for Computational Linguistics. ISSN 978-1-954085-05-3. p. 143–148.
• Dahl, Fredrik Andreas; Kasicheyanula, Taraka Rama; Hurlen, Petter; Brekke, Pål Haugar; Husby, Haldor & Gundersen, Tore [Show all 8 contributors for this article] (2021). Neural classification of Norwegian radiology reports: using NLP to detect findings in CT-scans of children. BMC Medical Informatics and Decision Making. ISSN 1472-6947. 21(1), p. 1–8. doi: 10.1186/s12911-021-01451-8. Full text in Research Archive
• Kutuzov, Andrei; Fomin, V.; Mikhailov, V. Nikola & Rodina, Julia (2020). Shiftry: Web service for diachronic analysis of Russian news. Komp'yuternaya Lingvistika i Intellektual'nye Tekhnologii. ISSN 2221-7932. 2020-(19), p. 500–516. doi: 10.28995/2075-7182-2020-19-500-516.
• Samuel, David & Straka, Milan (2020). ÚFAL at MRP 2020: Permutation-invariant Semantic Parsing in PERIN. In Oepen, Stephan; Abend, Omri; Abzianidze, Lasha; Bos, Johan; Hajic, Jan; Hershcovich, Daniel; Li, Bin; O'Gorman, Tim & Zeman, Daniel (Ed.), Proceedings of the CoNLL 2020 Shared Task:Cross-Framework Meaning Representation Parsing. Association for Computational Linguistics. ISSN 9781952148644. p. 53–64. doi: 10.18653/v1/2020.conll-shared.5.
• Katricheva, Nadezda; Yaskevich, Alyaxey; Lisitsina, Anastasiya; Zhordaniya, Tamara; Kutuzov, Andrei & Kuzmenko, Elizaveta (2020). Vec2graph: A Python Library for Visualizing Word Embeddings as Graphs. Communications in Computer and Information Science. ISSN 1865-0929. 1086, p. 190–198. doi: 10.1007/978-3-030-39575-9_20.
• Kurtz, Robin; Oepen, Stephan & Kuhlmann, Marco (2020). End-to-End Negation Resolution as Graph Parsing. In Bouma, Gosse; Matsumoto, Yuji; Oepen, Stephan; Sagae, Kenji; Seddah, Djame; Sun, Weiwei; Søgaard, Anders & Tsarfaty, Reut (Ed.), Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies. Association for Computational Linguistics. ISSN 978-1-952148-11-8. p. 14–24.
• Abzianidze, Lasha; Bos, Johan & Oepen, Stephan (2020). DRS at MRP 2020: Dressing up Discourse Representation Structures as Graphs. In Oepen, Stephan; Abend, Omri; Abzianidze, Lasha; Bos, Johan; Hajic, Jan; Hershcovich, Daniel; Li, Bin; O'Gorman, Tim & Zeman, Daniel (Ed.), Proceedings of the CoNLL 2020 Shared Task:Cross-Framework Meaning Representation Parsing. Association for Computational Linguistics. ISSN 9781952148644. p. 23–32. doi: 10.18653/v1/2020.conll-shared.2.
• Oepen, Stephan; Abend, Omri; Abzianidze, Lasha; Bos, Johan; Hajic, Jan & Hershcovich, Daniel [Show all 10 contributors for this article] (2020). MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing. In Oepen, Stephan; Abend, Omri; Abzianidze, Lasha; Bos, Johan; Hajic, Jan; Hershcovich, Daniel; Li, Bin; O'Gorman, Tim & Zeman, Daniel (Ed.), Proceedings of the CoNLL 2020 Shared Task:Cross-Framework Meaning Representation Parsing. Association for Computational Linguistics. ISSN 9781952148644. p. 1–22.
• Buljan, Maja; Nivre, Joakim; Oepen, Stephan & Øvrelid, Lilja (2020). A tale of three parsers: Towards diagnostic evaluation for meaning representation parsing. In Calzolari, Nicoletta (Eds.), Proceedings of the 12th Language Resources and Evaluation Conference . European Language Resources Association. ISSN 979-10-95546-34-4. p. 1902–1909. Full text in Research Archive
• Mareček, David; Celikkanat, Hande; Silfverberg, Miika; Ravishankar, Vinit & Tiedemann, Jörg (2020). Are Multilingual Neural Machine Translation Models Better at Capturing Linguistic Features? The Prague Bulletin of Mathematical Linguistics (PBML). ISSN 0032-6585. 115, p. 143–162. doi: 10.14712/00326585.009.
• Abdou, Mostafa; Ravishankar, Vinit; Barrett, Maria; Belinkov, Yonatan; Elliott, Desmond & Søgaard, Anders (2020). The Sensitivity of Language Models and Humans to Winograd Schema Perturbations. In Jurafsky, Dan; Chai, Joyce; Schluter, Natalie & Tetreault, Joel (Ed.), Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-952148-25-5. p. 7590–7604. doi: 10.18653/v1/2020.acl-main.679.
• Lauscher, Anne; Ravishankar, Vinit; Vulić, Ivan & Glavaš, Goran (2020). From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020. Association for Computational Linguistics. ISSN 978-1-952148-60-6. p. 4483–4499. doi: 10.18653/v1/2020.emnlp-main.363.
• Kulmizev, Artur; Ravishankar, Vinit; Abdou, Mostafa & Nivre, Joakim (2020). Do Neural Language Models Show Preferences for Syntactic Formalisms? In Jurafsky, Dan; Chai, Joyce; Schluter, Natalie & Tetreault, Joel (Ed.), Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-952148-25-5. p. 4077–4091. doi: 10.18653/v1/2020.acl-main.375.
• Touileb, Samia (2020). LTG-ST at NADI Shared Task 1: Arabic Dialect Identification using a Stacking Classifier. In Zitouni, Imed; Abdul-Mageed, Muhammad; Bouamor, Houda; Bougares, Fethi; El-Haj, Mahmoud; Tomeh, Nadi & Zaghouani, Wajdi (Ed.), Proceedings of the Fifth Arabic Natural Language Processing Workshop. Association for Computational Linguistics. ISSN 978-1-952148-38-5. p. 313–319.
• Touileb, Samia; Øvrelid, Lilja & Velldal, Erik (2020). Gender and sentiment, critics and authors: a dataset of Norwegian book reviews. In Costa-jussà, Marta R.; Hardmeier, Christian; Radford, Will & Webster, Kellie (Ed.), Proceedings of the Second Workshop on Gender Bias in Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-952148-43-9. p. 125–138.
• Kutuzov, Andrei & Giulianelli, Mario (2020). UiO-UvA at SemEval-2020 Task 1: Contextualised Embeddings for Lexical Semantic Change Detection, Proceedings of the Fourteenth Workshop on Semantic Evaluation. Association for Computational Linguistics. ISSN 978-1-952148-31-6. p. 126–134.
• Rodina, Julia & Kutuzov, Andrei (2020). RuSemShift: a dataset of historical lexical semantic change in Russian, Proceedings of the 28th International Conference on Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-952148-27-9. p. 1037–1047.
• Pilán, Ildikó; Brekke, Pål Haugar; Dahl, Fredrik Andreas; Gundersen, Tore; Husby, Haldor & Nytrø, Øystein [Show all 7 contributors for this article] (2020). Classification of Syncope Cases in Norwegian Medical Records. In Rumshisky, Anna; Roberts, Kirk; Bethard, Steven & Naumann, Tristan (Ed.), Proceedings of the 3rd Clinical Natural Language Processing Workshop . Association for Computational Linguistics. ISSN 978-1-952148-74-3. p. 79–84. doi: 10.18653/v1/2020.clinicalnlp-1.9.
• Navas-Alejo, Irean; Badia, Toni & Barnes, Jeremy (2020). Cross-lingual Emotion Intensity Prediction. In Nissim, Malvina; Patti, Viviana & Plank, Barbara (Ed.), Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media. Association for Computational Linguistics. ISSN 978-4-87974-723-5. p. 140–152.
• Adouane, Wafia; Touileb, Samia & Bernardy, Jean-Philippe (2020). Identifying Sentiments in Algerian Code-switched User-generated Comments. In Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan & Piperidis, Stelios (Ed.), Proceedings of The 12th Language Resources and Evaluation Conference. European Language Resources Association. ISSN 979-10-95546-34-4. p. 2698–2705.
• Øvrelid, Lilja; Mæhlum, Petter; Barnes, Jeremy & Velldal, Erik (2020). A Fine-Grained Sentiment Dataset for Norwegian. In Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan & Piperidis, Stelios (Ed.), Proceedings of The 12th Language Resources and Evaluation Conference. European Language Resources Association. ISSN 979-10-95546-34-4.
• Lison, Pierre; Barnes, Jeremy; Hubin, Aliaksandr & Touileb, Samia (2020). Named Entity Recognition without Labelled Data: A Weak Supervision Approach . In Jurafsky, Dan; Chai, Joyce; Schluter, Natalie & Tetreault, Joel (Ed.), Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-952148-25-5. p. 1518–1533. Full text in Research Archive
• Kunilovskaya, Maria; Kutuzov, Andrei & Plum, Alistair (2020). Taxonomy enrichment for Russian: synset classification outperforms linear hyponym-hypernym projections. Komp'yuternaya Lingvistika i Intellektual'nye Tekhnologii. ISSN 2221-7932. 19, p. 459–469. doi: 10.28995/2075-7182-2020-19-474-484.
• Kutuzov, Andrei; Fomin, Vadim; Rodina, Julia & Mikhailov, Vladislav (2020). ShiftRy: web service for diachronic analysis of Russian news. Komp'yuternaya Lingvistika i Intellektual'nye Tekhnologii. ISSN 2221-7932. 19, p. 485–501.
• Jørgensen, Fredrik; Aasmoe, Tobias; Husevåg, Anne-Stine Ruud; Øvrelid, Lilja & Velldal, Erik (2020). NorNE: Annotating Named Entities for Norwegian. In Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan & Piperidis, Stelios (Ed.), Proceedings of The 12th Language Resources and Evaluation Conference. European Language Resources Association. ISSN 979-10-95546-34-4. p. 4547–4556.
• Pilán, Ildikó; Brekke, Pål Haugar & Øvrelid, Lilja (2020). Building a Norwegian Lexical Resource for Medical Entity Recognition. In Melero, Maite (Eds.), Proceedings of the LREC 2020 Workshop on Multilingual Biomedical Text Processing (MultiligualBIO 2020). European Language Resources Association. ISSN 979-10-95546-65-8. p. 9–14.
• Logacheva, Varvara; Teslenko, Denis; Shelmanov, Artem; Remus, S.; Ustalov, Dmitry & Kutuzov, Andrei [Show all 10 contributors for this article] (2020). Word Sense Disambiguation for 158 Languages using Word Embeddings Only. In Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan & Piperidis, Stelios (Ed.), Proceedings of The 12th Language Resources and Evaluation Conference. European Language Resources Association. ISSN 979-10-95546-34-4. p. 5945–5954.
• Barnes, Jeremy Claude; Velldal, Erik & Øvrelid, Lilja (2020). Improving Sentiment Analysis with Multi-task Learning of Negation. Natural Language Engineering. ISSN 1351-3249. 1(21). doi: 10.1017/S1351324920000510.
• Berggren, Stig Johan; Rama, Taraka & Øvrelid, Lilja (2019). Regression or classification? Automated Essay Scoring for Norwegian. In Yannakoudakis, Helen; Kochmar, Ekaterina; Leacock, Claudia; Madnani, Nitin; Pilán, Ildikó & Zesch, Torsten (Ed.), Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications. Association for Computational Linguistics. ISSN 978-1-950737-34-5. p. 92–102.
• Koller, Alexander; Oepen, Stephan & Sun, Weiwei (2019). Graph-Based Meaning Representations: Design and Processing. In Nakov, Preslav & Palmer, Alexis (Ed.), The 57th Annual Meetingof the Association for Computational Linguistics: Tutorial Abstracts. Association for Computational Linguistics. ISSN 978-1-950737-50-5. p. 6–11. doi: 10.18653/v1/P19-4002.
• Kåsen, Andre; Hagen, Kristin; Nøklestad, Anders & Priestley, Joel (2019). Tagging a Norwegian Dialect Corpus. In Hartmann, Mareike & Plank, Barbara (Ed.), Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7929-995-8. p. 350–355. Full text in Research Archive
• Kutuzov, Andrei & Nikishina, Irina (2019). Double-Blind Peer-Reviewing and Inclusiveness in Russian NLP Conferences, Analysis of Images, Social Networks and Texts (Revised Selected Papers). Springer Publishing Company. ISSN 978-3-030-37334-4. p. 3–8. doi: 10.1007/978-3-030-37334-4_1.
• Droganova, Kira; Kutuzov, Andrei; Mediankin, Nikita & Zeman, Daniel (2019). ÚFAL-Oslo at MRP 2019: Garage Sale Semantic Parsing. In Oepen, Stephan; Abend, Omri; Hajic, Jan; Hershcovich, Daniel; Kuhlmann, Marco; O’Gorman, Tim & Nianwen, Xue (Ed.), Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics. ISSN 978-1-950737-60-4. p. 158–165. doi: 10.18653/v1/K19-2015.
• Oepen, Stephan & Flickinger, Dan (2019). The ERG at MRP 2019: Radically Compositional Semantic Dependencies. In Oepen, Stephan; Abend, Omri; Hajic, Jan; Hershcovich, Daniel; Kuhlmann, Marco; O’Gorman, Tim & Nianwen, Xue (Ed.), Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics. ISSN 978-1-950737-60-4. p. 40–44. doi: 10.18653/v1/K19-2003.
• Oepen, Stephan; Abend, Omri; Hajic, Jan; Hershcovich, Daniel; Kuhlmann, Marco & O'Gorman, Tim [Show all 10 contributors for this article] (2019). MRP 2019: Cross-Framework Meaning Representation Parsing. In Oepen, Stephan; Abend, Omri; Hajic, Jan; Hershcovich, Daniel; Kuhlmann, Marco; O’Gorman, Tim & Nianwen, Xue (Ed.), Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics. ISSN 978-1-950737-60-4. p. 1–27. doi: 10.18653/v1/K19-2001.

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• Tahmasebi, Nina; Montariol, Syrielle; Kutuzov, Andrei; Hengchen, Simon; Dubossarsky, Haim & Borin, Lars (2022). Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change. Association for Computational Linguistics. ISBN 978-1-955917-42-1. 219 p.
• Barnes, Jeremy (2021). Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics. ISBN 978-1-954085-46-6. 5953 p.
• Dobnik, Simon & Øvrelid, Lilja (2021). Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISBN 978-91-7929-614-8. 467 p.
• Kutuzov, Andrei; van der Aalst, Wil M. P.; Batagelj, Vladimir & Ignatov, Dmitry (2021). Proceedings of AIST 2020: Analysis of Images, Social Networks and Texts. Springer. ISBN 978-3-030-72610-2. 480 p.
• Bouma, Gosse; Matsumoto, Yuji; Oepen, Stephan; Sagae, Kenji; Seddah, Djame & Sun, Weiwei [Show all 8 contributors for this article] (2020). Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies. Association for Computational Linguistics. ISBN 978-1-952148-11-8. 265 p.
• Oepen, Stephan; Abend, Omri; Abzianidze, Lasha; Bos, Johan; Hajic, Jan & Hershcovich, Daniel [Show all 9 contributors for this article] (2020). Proceedings of the CoNLL 2020 Shared Task:Cross-Framework Meaning Representation Parsing. Association for Computational Linguistics. ISBN 9781952148644. 99 p.
• Oepen, Stephan; Abend, Omri; Hajic, Jan; Hershcovich, Daniel; Kuhlmann, Marco & O’Gorman, Tim [Show all 7 contributors for this article] (2019). Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics. ISBN 978-1-950737-60-4. 187 p.

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• Lison, Pierre; Rots, Aike Peter & De Korne, Haley (2022). Hvilket fremmedspråk bør man lære seg i Google-oversettelsenes tidsalder? Morgenbladet. ISSN 0805-3847.
• Lison, Pierre; Korsvoll, Nils Hallvard & Lundberg, Aase-Kristine Aasen (2022). Kjernekraft -er det farlig, eller er det fremtiden? Morgenbladet. ISSN 0805-3847.
• van der Aalst, Wil M. P.; Batagelj, Vladimir; Buzmakov, Alexey; Ignatov, Dmitry I.; Kalenkova, Anna & Khachay, Michael [Show all 18 contributors for this article] (2021). Preface. Communications in Computer and Information Science. ISSN 1865-0929. 1357, p. vii–x.
• Welzl, Michael; Oepen, Stephan; Cezary Jaskula, Cezary; Griwodz, Carsten & Islam, Safiqul (2021). Collaboration in the IETF: an initial analysis of two decades in email discussions. Computer communication review. ISSN 0146-4833. 51(3), p. 29–32. doi: 10.1145/3477482.3477488.
• Touileb, Samia; Øvrelid, Lilja & Velldal, Erik (2021). Using Gender- and Polarity-informed Models to Investigate Bias.
• Lison, Pierre; Bølstad, Jørgen & Kvellestad, Anders (2021). Forvirrende pandemistatistikk: Hva skal vi med logaritmer i grafer? Morgenbladet. ISSN 0805-3847.
• Velldal, Erik; Walsø, Claes Lyth & Øvrelid, Lilja (2021). Nå kan maskinene tolke hva du føler og mener. [Internet]. forskning,no.
• Velldal, Erik; Walsø, Claes Lyth & Øvrelid, Lilja (2021). Nå er maskinene klare til å tolke hva du føler og mener. [Internet]. titan.uio.no.
• Lison, Pierre (2021). Skweak: Weak Supervision Made Easy for NLP.
• Lison, Pierre (2021). Fremdrift i forskningsprosjekter.
• Lison, Pierre; Pilán, Ildikó; Sánchez Ruenes, David; Batet, Montserrat & Øvrelid, Lilja (2021). Anonymisation Models for Text Data: State of the art, Challenges and Future Directions.
• Lison, Pierre; Pilán, Ildikó; Øvrelid, Lilja; Sánchez Ruenes, David & Batet, Montserrat (2021). Anonymisation Models for Text Data: State of the art, Challenges and Future Directions. Show summary

  This position paper investigates the problem of automated text anonymisation, which is a prerequisite for secure sharing of documents containing sensitive information about individuals. We summarise the key concepts behind text anonymisation and provide a review of current approaches. Anonymisation methods have so far been developed in two fields with little mutual interaction, namely natural language processing and privacy-preserving data publishing. Based on a case study, we outline the benefits and limitations of these approaches and discuss a number of open challenges, such as (1) how to account for multiple types of semantic inferences, (2) how to strike a balance between disclosure risk and data utility and (3) how to evaluate the quality of the resulting anonymisation. We lay out a case for moving beyond sequence labelling models and incorporate explicit measures of disclosure risk into the text anonymisation process.

• Lison, Pierre; Barnes, Jeremy Claude & Hubin, Aliaksandr (2021). skweak: weak supervision made easy for NLP. Show summary

  We present skweak, a versatile, Python-based software toolkit enabling NLP developers to apply weak supervision to a wide range of NLP tasks. Weak supervision is an emerging machine learning paradigm based on a simple idea: instead of labelling data points by hand, we use labelling functions derived from domain knowledge to automatically obtain annotations for a given dataset. The resulting labels are then aggregated with a generative model that estimates the accuracy (and possible confusions) of each labelling function. The skweak toolkit makes it easy to implement a large spectrum of labelling functions (such as heuristics, gazetteers, neural models or linguistic constraints) on text data, apply them on a corpus, and aggregate their results in a fully unsupervised fashion. skweak is especially designed to facilitate the use of weak supervision for NLP tasks such as text classification and sequence labelling. We illustrate the use of skweak for NER and sentiment analysis. skweak is released under an open-source license and is available at https://github.com/NorskRegnesentral/skweak

• Lison, Pierre & Falkum, Ingrid Lossius (2020). Hva skjedde med «Don’t be evil»? Morgenbladet. ISSN 0805-3847.
• Lison, Pierre (2020). Named Entity Recognition without Labelled Data: A Weak Supervision Approach.
• Løland, Anders; Lison, Pierre & Falkum, Ingrid Lossius (2020). Episode 6: Kan språkteknologi virkelig forstå språk? Med Ingrid Lossius Falkum og Pierre Lison. [Internet]. Sannsynligvis VIKTIG (podkast).
• Løland, Anders & Lison, Pierre (2020). Episode 5: Hva er språkteknologi (eller NLP)? Med Pierre Lison. [Internet]. Sannsynligvis VIKTIG (podkast).
• Pilán, Ildikó; Brekke, Pål H. & Øvrelid, Lilja (2020). Building a Norwegian Lexical Resource for Medical Entity Recognition. Show summary

  We present a large Norwegian lexical resource of categorized medical terms. The resource, which merges information from large medical databases, contains over 56,000 entries, including automatically mapped terms from a Norwegian medical dictionary. We describe the methodology behind this automatic dictionary entry mapping based on keywords and suffixes and further present the results of a manual evaluation performed on a subset by a domain expert. The evaluation indicated that ca. 80% of the mappings were correct.

• Prévot, Laurent; Magistry, Pierre & Lison, Pierre (2019). Should we use movie subtitles to study linguistic patterns of conversational speech? A study based on French, English and Taiwan Mandarin.
• Øvrelid, Lilja (2019). Forskjeller mellom talemål og skrift. Hva kan trebanker fortelle oss?
• Rønningstad, Egil & Øvrelid, Lilja (2020). Targeted Sentiment Analysis for Norwegian text. Universitetet i Oslo.
• Strand, Håvard; Velldal, Erik & Landsverk, Peder (2019). Partial Automation of the Data-collection Process. University of Oslo.

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