Lilja Øvrelid

• 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: https%3A/doi.org/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.

• 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.
• 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.
• 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.
• 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.
• 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.
• Brekke, Pål Haugar; Rama, Taraka; Pilán, Ildikó; Nytrø, Øystein & Øvrelid, Lilja (2021). Synthetic data for annotation and extraction of family history information from clinical text. Journal of Biomedical Semantics. ISSN 2041-1480. 12(11). doi: 10.1186/s13326-021-00244-2. Full text in Research Archive
• 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.
• 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
• 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
• 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.
• 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.
• 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.
• 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.
• 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.
• Hammer, Hugo Lewi; Riegler, Michael Alexander; Øvrelid, Lilja & Velldal, Erik (2019). THREAT: A Large Annotated Corpus for Detection of Violent Threats, Proceedings of Content Based Multimedia Information (CBMI 2019). IEEE conference proceedings. ISSN 978-1-7281-4673-7. p. 1–5. doi: 10.1109/CBMI.2019.8877435.
• Ravishankar, Vinit; Gökirmak, Memduh; Øvrelid, Lilja & Velldal, Erik (2019). Multilingual Probing of Deep Pre-Trained Contextual Encoders. In Nivre, Joakim; Derczynski, Leon; Ginter, Filip; Lindi, Bjørn; Oepen, Stephan; Søgaard, Anders & Tidemann, Jorg (Ed.), Proceedings of the First NLPL Workshop on Deep Learning for Natural Language Processing. Linköping University Electronic Press. ISSN 978-91-7929-999-6. p. 37–47.
• Nooralahzadeh, Farhad; Lønning, Jan Tore & Øvrelid, Lilja (2019). Reinforcement-based denoising of distantly supervised NER with partial annotation, Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019). Association for Computational Linguistics. ISSN 978-1-950737-789. p. 225–234. doi: DOI%3A%2010.18653/v1/D19-6125. Full text in Research Archive
• Mæhlum, Petter; Barnes, Jeremy Claude; Øvrelid, Lilja & Velldal, Erik (2019). Annotating evaluative sentences for sentiment analysis: a dataset for Norwegian. 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. 121–130. Full text in Research Archive
• Barnes, Jeremy Claude; Touileb, Samia; Øvrelid, Lilja & Velldal, Erik (2019). Lexicon information in neural sentiment analysis: a multi-task learning approach. 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. 175–186. Full text in Research Archive
• Ravishankar, Vinit; Øvrelid, Lilja & Velldal, Erik (2019). Probing Multilingual Sentence Representations With X-Probe. In Augenstein, Isabelle; Gella, Spandana; Ruder, Sebastian; Can, Burcu; Welbl, Johannes; Ren, Xiang & Rei, Marek (Ed.), The 4th Workshop on Representation Learning for NLP (RepL4NLP-2019) : Proceedings of the Workshop. Association for Computational Linguistics. ISSN 978-1-950737-35-2. p. 156–168. doi: 10.18653/v1/W19-4318.
• Barnes, Jeremy Claude; Øvrelid, Lilja & Velldal, Erik (2019). Sentiment analysis is not solved! Assessing and probing sentiment classification. In Linzen, Tal; Chrupała, Grzegorz; Belinkov, Yonatan & Hupkes, Dieuwke (Ed.), The BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP at ACL 2019: Proceedings of the Second Workshop. Association for Computational Linguistics. ISSN 978-1-950737-30-7. p. 12–23. doi: 10.18653/v1/w19-4802. Full text in Research Archive
• Kutuzov, Andrei; Velldal, Erik & Øvrelid, Lilja (2019). One-to-X Analogical Reasoning on Word Embeddings: a Case for Diachronic Armed Conflict Prediction from News Texts. In Tahmasebi, Nina; Borin, Lars; Jatowt, Adam & Xu, Yang (Ed.), Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change. Association for Computational Linguistics. ISSN 978-1-950737-31-4. p. 196–201. doi: 10.18653/v1/W19-4724. Full text in Research Archive
• Fares, Murhaf; Oepen, Stephan; Øvrelid, Lilja; Björne, Jari & Johansson, Richard (2018). The 2018 Shared Task on Extrinsic Parser Evaluation: On the Downstream Utility of English Universal Dependency Parsers. In Zeman, Daniel & Hajic, Jan (Ed.), Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Association for Computational Linguistics. ISSN 978-1-948087-82-7. p. 22–33. doi: 10.18653/v1/K18-2002.
• Stadsnes, Cathrine; Øvrelid, Lilja & Velldal, Erik (2018). Evaluating Semantic Vectors for Norwegian. NIKT: Norsk IKT-konferanse for forskning og utdanning. ISSN 1892-0713. Show summary

  In this article, we present two benchmark data sets for evaluating models of semantic word similarity for Norwegian. While such resources are available for English, they did not exist for Norwegian prior to this work. Furthermore, we produce large-coverage semantic vectors trained on the Norwegian Newspaper Corpus using several popular word embedding frameworks. Finally, we demonstrate the usefulness of the created resources for evaluating performance of different word embedding models on the tasks of analogical reasoning and synonym detection. The benchmark data sets and word embeddings are all made freely available.

• Nooralahzadeh, Farhad & Øvrelid, Lilja (2018). SIRIUS-LTG: An Entity Linking Approach to Fact Extraction and Verification, Proceedings of the First Workshop on Fact Extraction and VERification (FEVER) . Association for Computational Linguistics. ISSN 978-1-948087-73-5. p. 119–123. doi: 10.18653/v1/w18-5519.
• Bouma, Gosse; Hajic, Jan; Haug, Dag Trygve Truslew; Nivre, Joakim; Solberg, Per Erik & Øvrelid, Lilja (2018). Expletives in Universal Dependency Treebanks, Proceedings of the Second Workshop on Universal Dependencies (UDW 2018). Association for Computational Linguistics. ISSN 978-1-948087-780. p. 18–26. doi: 10.18653/v1/w18-6003.
• Kasicheyanula, Taraka Rama; Brekke, Pål Haugar; Nytrø, Øystein & Øvrelid, Lilja (2018). Iterative development of family history annotation guidelines using a synthetic corpus of clinical text, Proceedings of the 9th International Workshop on Health Text Mining and Information Analysis (LOUHI 2018). Association for Computational Linguistics. ISSN 978-1-948087-74-2. p. 111–121. doi: 10.18653/v1/w18-5613.
• Kutuzov, Andrei; Øvrelid, Lilja; Szymanski, Terrence & Velldal, Erik (2018). Diachronic word embeddings and semantic shifts: a survey, Proceedings of the 27th International Conference on Computational Linguistics. Association for Computational Linguistics. ISSN 978-1-948087-50-6. p. 1384–1397. Full text in Research Archive
• Nooralahzadeh, Farhad & Øvrelid, Lilja (2018). Syntactic Dependency Representations in Neural Relation Classification. In Dinu, Georgiana; Ballesteros, Miguel; Sil, Avirup; Bowman, Sam; Hamza, Wael; Søgaard, Anders; Naseem, Tahira & Goldberg, Yoav (Ed.), Proceedings of the Workshop on the Relevance of Linguistic Structure in Neural Architectures for NLP. Association for Computational Linguistics. ISSN 978-1-948087-42-1. doi: 10.18653/v1/w18-2907.
• Nooralahzadeh, Farhad; Øvrelid, Lilja & Lønning, Jan Tore (2018). SIRIUS-LTG-UiO at SemEval-2018 Task 7: Convolutional Neural Networks with Shortest Dependency Paths for Semantic Relation Extraction and Classification in Scientific Papers, Proceedings of the 12th International Workshop on Semantic Evaluation. Association for Computational Linguistics. ISSN 978-1-948087-20-9. p. 805–811. doi: 10.18653/v1/S18-1128.
• Nooralahzadeh, Farhad; Øvrelid, Lilja & Lønning, Jan Tore (2018). Evaluation of Domain-specific Word Embeddings using Knowledge Resources. In Calzolari, Nicoletta; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Hasida, Koiti; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan; Piperidis, Stelios & Tokunaga, Takenobu (Ed.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation. European Language Resources Association. ISSN 979-10-95546-00-9. p. 1438–1445.
• Øvrelid, Lilja; Kåsen, Andre; Hagen, Kristin; Solberg, Per Erik; Johannessen, Janne Bondi & Nøklestad, Anders (2018). The LIA Treebank of Spoken Norwegian Dialects. In Calzolari, Nicoletta; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Hasida, Koiti; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan; Piperidis, Stelios & Tokunaga, Takenobu (Ed.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation. European Language Resources Association. ISSN 979-10-95546-00-9. p. 4482–4488. Full text in Research Archive
• Velldal, Erik; Øvrelid, Lilja; Bergem, Eivind Alexander; Stadsnes, Cathrine; Touileb, Samia & Jørgensen, Fredrik (2018). NoReC: The Norwegian Review Corpus. In Calzolari, Nicoletta; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Hasida, Koiti; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan; Piperidis, Stelios & Tokunaga, Takenobu (Ed.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation. European Language Resources Association. ISSN 979-10-95546-00-9. p. 4186–4191. Full text in Research Archive
• Lapponi, Emanuele; Oepen, Stephan & Øvrelid, Lilja (2017). EPE 2017: The Sherlock Negation Resolution Downstream Application. In Oepen, Stephan (Eds.), Proceedings of the 2017 Shared Task on Extrinsic Parser Evaluation at the Fourth International Conference on Dependency Linguistics and the 15th International Conference on Parsing Technologies. Association for Computational Linguistics. ISSN 978-1-945626-74-6. p. 25–30.
• Oepen, Stephan; Øvrelid, Lilja; Björne, Jari; Johansson, Richard; Lapponi, Emanuele & Ginter, Filip [Show all 7 contributors for this article] (2017). The 2017 Shared Task on Extrinsic Parser Evaluation: Towards a Reusable Community Infrastructure. In Oepen, Stephan (Eds.), Proceedings of the 2017 Shared Task on Extrinsic Parser Evaluation at the Fourth International Conference on Dependency Linguistics and the 15th International Conference on Parsing Technologies. Association for Computational Linguistics. ISSN 978-1-945626-74-6. p. 1–16. doi: 10.18653/v1/k18-2002.
• Kutuzov, Andrei; Velldal, Erik & Øvrelid, Lilja (2017). Temporal dynamics of semantic relations in word embeddings: an application to predicting armed conflict participants, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. ISSN 978-1-945626-83-8. p. 1825–1830. doi: 10.18653/v1/D17-1194. Full text in Research Archive
• Kutuzov, Andrei; Velldal, Erik & Øvrelid, Lilja (2017). Tracing armed conflicts with diachronic word embedding models. In Caselli, Tommaso (Eds.), Proceedings of the Events and Stories in the News Workshop. Association for Computational Linguistics. ISSN 978-1-945626-63-0. p. 31–36. doi: 10.18653/v1/W17-2705. Full text in Research Archive
• Enger, Martine; Velldal, Erik & Øvrelid, Lilja (2017). An open-source tool for negation detection: a maximum-margin approach. In Blanco, Eduardo; Morante, Roser & Saurí, Roser (Ed.), Proceedings of the Workshop on Computational Semantics Beyond Events and Roles. Association for Computational Linguistics. ISSN 978-1-945626-49-4. p. 64–69. doi: 10.18653/v1/w17-1810.
• Sand, Heidi Marion; Velldal, Erik & Øvrelid, Lilja (2017). Wordnet extension via word embeddings: Experiments on the Norwegian Wordnet. In Tiedemann, Jörg (Eds.), Proceedings of the 21st Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7685-601-7. p. 298–302. Full text in Research Archive
• Hohle, Petter; Øvrelid, Lilja & Velldal, Erik (2017). Optimizing a PoS Tagset for Norwegian Dependency Parsing. In Tiedemann, Jörg (Eds.), Proceedings of the 21st Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7685-601-7. p. 142–151. Full text in Research Archive
• Velldal, Erik; Øvrelid, Lilja & Hohle, Petter (2017). Joint UD Parsing of Norwegian Bokmål and Nynorsk. In Tiedemann, Jörg (Eds.), Proceedings of the 21st Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 978-91-7685-601-7. p. 1–10. Full text in Research Archive
• Oepen, Stephan; Read, Jonathon; Scheffler, Tatjana; Sidarenka, Uladzimir; Stede, Manfred & Velldal, Erik [Show all 7 contributors for this article] (2016). OPT: Oslo–Potsdam–Teesside. Pipelining Rules, Rankers, and Classifier Ensembles for Shallow Discourse Parsing. In Xue, Nianwen (Eds.), Proceedings of the CoNLL-16 Shared Task. Association for Computational Linguistics. ISSN 978-1-932432-66-4. p. 20–26. doi: 10.18653/v1/k16-2002.
• Ivanova, Angelina; Oepen, Stephan; Dridan, Rebecca; Flickinger, Dan; Øvrelid, Lilja & Lapponi, Emanuele (2016). On different approaches to syntactic analysis into bi-lexical dependencies: An empirical comparison of direct, PCFG-based, and HPSG-based parsers. Journal of Language Modelling. ISSN 2299-856X. 4(1), p. 113–144. doi: 10.15398/jlm.v4i1.101.
• Wester, Aksel Ladegård; Øvrelid, Lilja; Velldal, Erik & Hammer, Hugo Lewi (2016). Threat detection in online discussions, Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA@NAACL-HLT 2016 (WASSA 2016). Association for Computational Linguistics. ISSN 978-1-941643-82-2. p. 66–71. doi: 10.18653/v1/w16-0413.
• Kutuzov, Andrei; Velldal, Erik & Øvrelid, Lilja (2016). Redefining part-of-speech classes with distributional semantic models, Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning (CoNLL). Association for Computational Linguistics. ISSN 978-1-945626-19-7. p. 115–125. doi: 10.18653/v1/K16-1012. Full text in Research Archive
• Øvrelid, Lilja & Hohle, Petter (2016). Universal Dependencies for Norwegian, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). European Language Resources Association. ISSN 978-2-9517408-9-1. p. 1579–1585.
• Lien, Jostein; Velldal, Erik & Øvrelid, Lilja (2015). Improving cross-domain dependency parsing with dependency-derived clusters. In Megyesi, Beáta (Eds.), Proceedings of the 20th Nordic Conference of Computational Linguistics. Linköping University Electronic Press. ISSN 978-91-7519-098-3. p. 117–126. Full text in Research Archive
• Hammer, Hugo Lewi; Solberg, Per Erik & Øvrelid, Lilja (2014). Sentiment classification of online political discussions: a comparison of a word-based and dependency-based method. In Balahur, Alexandra (Eds.), 5th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Association for Computational Linguistics. ISSN 978-1-634392-06-8. p. 90–96. doi: 10.3115/v1/w14-2616. Full text in Research Archive
• Solberg, Per Erik; Skjærholt, Arne; Øvrelid, Lilja; Hagen, Kristin & Johannessen, Janne Bondi (2014). The Norwegian Dependency Treebank. In Calzolari, Nicoletta; Choukri, Khalid; Declerck, Thierry; Loftsson, Hrafn; Maegaard, Bente; Mariani, Joseph; Moreno, Asuncion; Odijk, Jan & Piperidis, Stelios (Ed.), Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14). European Language Resources Association. ISSN 978-2-9517408-8-4. p. 789–795. Full text in Research Archive
• Ivanova, Angelina; Oepen, Stephan; Dridan, Rebecca; Flickinger, Dan & Øvrelid, Lilja (2013). On Different Approaches to Syntactic Analysis Into Bi-Lexical Dependencies. An Empirical Comparison of Direct, PCFG-Based, and HPSG-Based Parsers. In Bunt, Harry; Sima’an, Khalil & Huang, Liang (Ed.), Proceedings of The 13th International Conference on Parsing Technologies IWPT-2013. Association for Computational Linguistics. ISSN 978-1-937284-76-3. Full text in Research Archive
• Ivanova, Angelina; Oepen, Stephan & Øvrelid, Lilja (2013). Survey on parsing three dependency representations for English. In Dey, Anik; Krause, Sebastian; Nikolova, Ivelina; Vecchi, Eva; Bethard, Steven; Nakov, Preslav I. & Xu, Feiyu (Ed.), 51st Annual Meeting of the Association for Computational Linguistics Proceedings of the Student Research Workshop. Association for Computational Linguistics. ISSN 978-1-937284-53-4. p. 31–37.
• Øvrelid, Lilja & Skjærholt, Arne (2012). Lexical Categories for Improved Parsing of Web Data. International Conference on Computational Linguistics (ICCL) (COLING). ISSN 1525-2477. p. 903–912.
• Skjærholt, Arne & Øvrelid, Lilja (2012). Impact of Treebank Characteristics on Cross-Lingual Parser Adaptation. In Hendrickx, Iris; Kübler, Sandra & Simov, Kiril (Ed.), Proceedings of the Eleventh International Workshop on Treebanks and Linguistic Theories (TLT11). Edições Colibri. ISSN 978‐989‐689‐274‐6. p. 187–198.
• Lapponi, Emanuele; Read, Jonathon & Øvrelid, Lilja (2012). Representing and Resolving Negation for Sentiment Analysis, The 12th IEEE International Conference on Data Mining Workshops. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-0-7695-4925-5. p. 687–692. doi: 10.1109/icdmw.2012.23.
• Ivanova, Angelina; Oepen, Stephan; Øvrelid, Lilja & Flickinger, Dan (2012). Who Did What to Whom? A Contrastive Study of Syntacto-Semantic Dependencies. In Ide, Nancy & Xia, Fei (Ed.), Proceedings of the Sixth Linguistic Annotation Workshop. Association for Computational Linguistics. ISSN 978-1-937284-32-9. p. 2–11.
• Read, Jonathon; Velldal, Erik & Øvrelid, Lilja (2012). Topic classification for Suicidology. Journal of Computing Science and Engineering. ISSN 1976-4677. 6(2), p. 143–150. doi: 10.5626/JCSE.2012.6.2.143.
• Velldal, Erik; Øvrelid, Lilja; Read, Jonathon & Oepen, Stephan (2012). Speculation and Negation: Rules, Rankers, and the Role of Syntax. Computational Linguistics. ISSN 0891-2017. 38(2), p. 369–410. doi: 10.1162/COLI_a_00126. Show summary

  This article explores a combination of deep and shallow approaches to the problem of resolving the scope of speculation and negation within a sentence, specifically in the domain of biomedical research literature. The first part of the article focuses on speculation. After first showing how speculation cues can be accurately identified using a very simple classifier informed only by local lexical context, we go on to explore two different syntactic approaches to resolving the in-sentence scopes of these cues. Whereas one uses manually crafted rules operating over dependency structures, the other automatically learns a discriminative ranking function over nodes in constituent trees. We provide an in-depth error analysis and discussion of various linguistic properties characterizing the problem, and show that although both approaches perform well in isolation, even better results can be obtained by combining them, yielding the best published results to date on the CoNLL-2010 Shared Task data. The last part of the article describes how our speculation system is ported to also resolve the scope of negation.With only modest modifications to the initial design, the system obtains state-of-the-art results on this task also.

• Lapponi, Emanuele; Velldal, Erik; Øvrelid, Lilja & Read, Jonathon (2012). UiO2: Sequence-labeling Negation Using Dependency Features. In Agirre, Eneko; Bos, Johan & Diab, Mona (Ed.), *SEM 2012: The First Joint Conference on Lexical and Computational Semantics --- Volume 1: Proceedings of the main conference and the shared task. Association for Computational Linguistics. ISSN 978-1-937284-21-3. p. 319–327.
• Read, Jonathon; Velldal, Erik; Øvrelid, Lilja & Oepen, Stephan (2012). UiO1: Constituent-Based Discriminative Ranking for Negation Resolution. In Agirre, Eneko; Bos, Johan & Diab, Mona (Ed.), *SEM 2012: The First Joint Conference on Lexical and Computational Semantics --- Volume 1: Proceedings of the main conference and the shared task. Association for Computational Linguistics. ISSN 978-1-937284-21-3. p. 310–318.
• Read, Jonathon; Flickinger, Dan; Dridan, Rebecca; Oepen, Stephan & Øvrelid, Lilja (2012). The WeSearch Corpus, Treebank and Treecache: A Comprehensive Sample of User-Generated Content. In Calzolari, Nicoletta; Choukri, Khalid; Declerck, Thierry; Ugur Dogan, Mehmet; Maegaard, Bente; Mariani, Joseph & Odijk, Jan (Ed.), Proceedings of the Eighth International Conference on Language Resources and Evaluation. European Language Resources Association. ISSN 978-2-9517408-7-7.
• Read, Jonathon; Velldal, Erik & Øvrelid, Lilja (2012). Labeling Emotions in Suicide Notes: Cost-Sensitive Learning with Heterogeneous Features. Biomedical Informatics Insights. ISSN 1178-2226. 5, p. 99–103. doi: 10.4137/BII.S8930.
• Read, Jonathon; Velldal, Erik & Øvrelid, Lilja (2011). Topic classification for suicidology. In Gao, Helena Hong & Dong, Minghui (Ed.), Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation, and the Fourth International Symposium on Languages in Biology and Medicine. Pacific Asia Conference on Language, Information and Computation. ISSN 978-4-905166-02-3. p. 78–85. doi: 10.5626/jcse.2012.6.2.143.
• Read, Jonathon; Velldal, Erik; Oepen, Stephan & Øvrelid, Lilja (2011). Resolving speculation and negation scope in biomedical articles with a syntactic constituent ranker. In Gao, Helena Hong & Dong, Minghui (Ed.), Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation, and the Fourth International Symposium on Languages in Biology and Medicine. Pacific Asia Conference on Language, Information and Computation. ISSN 978-4-905166-02-3.
• Spreyer, Kathrin; Øvrelid, Lilja & Kuhn, Jonas (2010). Training Parsers on Partial Trees: A Cross-language Comparison. In Calzolari, Nicoletta; Choukri, Khalid; Maegaard, Bente; Mariani, Joseph; Odijk, Jan; Piperidis, Stelios; Rosner, Mike & Tapias, Daniel (Ed.), Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10). European Language Resources Association. ISSN 2-9517408-6-7.
• Bouma, Gerlof; Øvrelid, Lilja & Jonas, Kuhn (2010). Towards a Large Parallel Corpus of Cleft Constructions. In Calzolari, Nicoletta; Choukri, Khalid; Maegaard, Bente; Mariani, Joseph; Odijk, Jan; Piperidis, Stelios; Rosner, Mike & Tapias, Daniel (Ed.), Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10). European Language Resources Association. ISSN 2-9517408-6-7.
• Seeker, Wolfgang; Bernd, Bohnet; Øvrelid, Lilja & Jonas, Kuhn (2010). Informed ways of improving data-driven dependency parsing for German. In Jurafsky, Dan (Eds.), Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010). Daheng Electronic Press. ISSN 978-7-900268-00-6. p. 1122–1130.
• Øvrelid, Lilja; Velldal, Erik & Oepen, Stephan (2010). Syntactic Scope Resolution in Uncertainty Analysis. In Jurafsky, Dan (Eds.), Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010). Daheng Electronic Press. ISSN 978-7-900268-00-6. p. 1379–1387.
• Velldal, Erik; Øvrelid, Lilja & Oepen, Stephan (2010). Resolving Speculation: MaxEnt Cue Classification and Dependency-Based Scope Rules. In Farkas, Richárd (Eds.), Proceedings of the Fourteenth Conference on Computational Natural Language Learning -- Shared Task. Association for Computational Linguistics. ISSN 978-1-932432-84-8. p. 48–55.
• Øvrelid, Lilja; Spreyer, Kathrin & Kuhn, Jonas (2009). Improving Data-Driven Dependency Parsing Using Large-Scale LFG Grammars. In Su, Jian & Wiebe, Janyce (Ed.), Proceedings of the 47th Annual Meeting of ACL and 4th International Joint Conference on NLP (ACL-IJCNLP 2009). Association for Computational Linguistics. ISSN 978-1-932432-45-9.
• Øvrelid, Lilja; Spreyer, Kathrin & Kuhn, Jonas (2009). Cross-framework parser stacking for data-driven dependency parsing. Revue TAL. ISSN 1248-9433. 50(3), p. 109–138.

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• 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.

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• Touileb, Samia; Øvrelid, Lilja & Velldal, Erik (2021). Using Gender- and Polarity-informed Models to Investigate Bias.
• 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; 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.

• 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.

• Øvrelid, Lilja (2019). Forskjeller mellom talemål og skrift. Hva kan trebanker fortelle oss?
• Dahl, Fredrik Andreas; Kasicheyanula, Taraka Rama; Hurlen, Petter; Brekke, Pål Haugar; Husby, Haldor & Gundersen, Tore [Show all 8 contributors for this article] (2019). Classifying Norwegian radiology reports with deep learning.
• Øvrelid, Lilja (2012). Constituent-based discriminative ranking for negation resolution.
• Øvrelid, Lilja (2010). Training Parsers on Partial Trees: A Cross-language Comparison.
• Øvrelid, Lilja (2010). Towards a Large Parallel Corpus of Cleft Constructions.
• Øvrelid, Lilja (2010). Syntactic Scope Resolution in Uncertainty Analysis.
• Rønningstad, Egil & Øvrelid, Lilja (2020). Targeted Sentiment Analysis for Norwegian text. Universitetet i Oslo.

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