Anders Nøklestad

• Honkapohja, Alpo; Thaisen, Jacob & Nøklestad, Anders (2024). A search tool based on language modelling developed for The Index of Middle English Prose. Open Research Europe. 3. doi: 10.12688/openreseurope.16590.2. Full text in Research Archive Show summary

  Non-standardised early vernaculars present a problem for search tools due to the high degree of variation. The challenge lies in the variation found in orthography, syntax, and lexicon between titles, incipits, and explicits in manuscript copies of the same work. Traditional search methods relying on exact string matching or regular expressions fail to address these variations comprehensively. This project presents a web-based search tool specifically designed to handle linguistic and textual variation. The software is made available as a part of the Index of Middle English Prose (IMEP). The search tool addresses the issue of variation by utilizing a database of incipits and explicits, character-based n-gram language models (LMs) built with the Stanford Research Institute Language Modelling (SRILM) toolkit, and a fuzzy search script (IMEP: FSS) written in Python. The tool optimizes for recall, retrieving multiple potential matches for a search string, without attempting to identify the ‘correct’ one. The search process involves looking up exact matches in the database while simultaneously using the fuzzy search script to evaluate the incipits and explicits against a model of the search string, followed by a match of the search string against models of the incipits and explicits. This two-step process shortens the processing time, which would otherwise be unreasonably long, because while using SRILM to match the search string against each incipit or explicit in the IMEP for precision could be time-consuming, running a first step where all texts are matched against a single LM built from the search string allows for faster processing. A web application, built using Django and Docker, combines the results of the direct database lookup and the fuzzy search script, presenting them as a list with exact matches followed by fuzzy matches ordered by increasing model perplexity. The tool is made available Open Access and can be adapted to other datasets.

• Priestley, Joel; Nøklestad, Anders; Hagen, Kristin; Laanemets, Anu & Haug, Dag Trygve Truslew (2024). Treebanks for the ordinary working grammarian. CEUR Workshop Proceedings. 3834, p. 313–321. Full text in Research Archive Show summary

  In this paper we present how three treebanks of Norwegian have been incorporated in the Glossa search interface, allowing users without specialized training to formulate queries based on syntactic information. One of the treebanks contains written material (mostly newspaper text, but also blogs, magazines and other genres) and the two other treebanks are based on transcriptions of spoken dialects. The user interface is simple and only allows access to selected features of the annotation. We show through two case studies how it can nevertheless be useful for the large group linguists who do not have the time or inclination to learn a full treebank query language. We argue that our tool fills an important gap and can help bring treebank data to new users.

• Haug, Dag Trygve Truslew; Yildirim, Ahmet; Hagen, Kristin & Nøklestad, Anders (2023). Rules and neural nets for morphological tagging of Norwegian - Results and challenges. In Alumäe, Tanel & Fishel, Mark (Ed.), Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa). University of Tartu. ISSN 9789916219997. p. 425–435. Full text in Research Archive Show summary

  This paper reports on efforts to improve the Oslo-Bergen Tagger for Norwegian morphological tagging. We train two deep neural network-based taggers using the recently introduced Norwegian pre-trained encoder (a BERT model for Norwegian). The first network is a sequence-to-sequence encoder-decoder and the second is a sequence classifier. We test both these configurations in a hybrid system where they combine with the existing rule-based system, and on their own. The sequence-to-sequence system performs better in the hybrid configuration, but the classifier system performs so well that combining it with the rules is actually slightly detrimental to performance.

• 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. International Conference on Computational Linguistics (ICCL) (COLING). ISSN 1525-2477. 29(7), p. 48–60. Full text in Research Archive Show summary

  Published in: Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC): https://aclanthology.org/venues/coling/. We present the Norwegian Anaphora Resolution Corpus (NARC), the first publicly available corpus annotated with anaphoric relations between noun phrases for Norwegian. The paper describes the annotated data for 326 documents in Norwegian Bokmål, together with inter-annotator agreement and discussions of relevant statistics. We also present preliminary modelling results which are comparable to existing corpora for other languages, and discuss relevant problems in relation to both modelling and the annotations themselves.

• Lane, Pia; Hagen, Kristin; Nøklestad, Anders & Priestley, Joel (2022). Creating a corpus for Kven, a minority language in Norway. Nordlyd. ISSN 0332-7531. 46(1), p. 159–170. doi: 10.7557/12.6345. Full text in Research Archive Show summary

  Language documentation, including the development and use of corpora, is frequently linked to revitalisation. This is also the case for the Kven language, a Finnic minoritised language, traditionally spoken in the two northernmost counties of Norway. Kven is a recognised minority language in Norway, protected by the European Charter for Regional or Minority Languages. This status led to increased efforts to document Kven, including the development of the Ruija Corpus, consisting of recordings of interviews in Kven. The corpus was an important tool for the standardisation of Kven. In this article we describe how the corpus was developed and account for search functions, including a discussion of the limitations of the corpus. We also discuss the role of corpora and other online tools for language revitalisation, with a particular focus on the standardisation of Kven and conclude by reflecting on how expertise also resides with the speakers of an endangered language and that they have a right to be involved in efforts of language documentation and revitalisation.

• Kåsen, Andre; Hagen, Kristin; Nøklestad, Anders; Priestley, Joel; Solberg, Per Erik & Haug, Dag Trygve Truslew (2022). The Norwegian Dialect Corpus Treebank. 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 Thirteenth Language Resources and Evaluation Conference. European Language Resources Association. ISSN 9791095546726. p. 4827–4832. Full text in Research Archive Show summary

  This paper presents the NDC Treebank of spoken Norwegian dialects in the Bokmal variety of Norwegian. It consists of dialect ˚ recordings made between 2006 and 2012 which have been digitised, segmented, transcribed and subsequently annotated with morphological and syntactic analysis. The nature of the spoken data gives rise to various challenges both in segmentation and annotation. We follow earlier efforts for Norwegian, in particular the LIA Treebank of spoken dialects transcribed in the Nynorsk variety of Norwegian, in the annotation principles to ensure interusability of the resources. We have developed a spoken language parser on the basis of the annotated material and report on its accuracy both on a test set across the dialects and by holding out single dialects.

• Borthen, Kaja; Søfteland, Åshild; Kveen, Perlaug Marie; Karagjosova, Elena & Nøklestad, Anders (2021). Finalpartiklar i norske talemål: Ei undersøking av variasjon knytt til geografi, alder og kjønn. Maal og Minne. ISSN 0024-855X. 113(1), p. 1–63. Full text in Research Archive Show summary

  This article reports on a study of geographical and demographical aspects of 46 final particles in Norwegian dialects, among them gitt (< lit.‘boy’), sant (< lit. ‘true’) and kan du skjønne (< lit. ‘can you realize’). In the first part of the study, a questionnaire was used as the method. The results from this study show to what extent informants from different regions in Norway report on use of the given final particles. The second part of the study is an investigation of the use of the 46 final particles in the corpora Nordisk dialektkorpus and LIA norsk. In sum, the study shows that i) many of the 46 final particles are delimited geographically; ii) some of the expressions are used to greater extent by the older informants than by the younger ones, and the other way around; iii) a few expressions have a more frequent use among men than among women, and the other way around, and iv) overall, younger people seem to place expressions in the final (tag) position more often than do older people when more than one syntactic position is possible. In addition, the study contributes insights into the two methods that were used.

• Søfteland, Åshild; Nøklestad, Anders; Priestley, Joel & Hagen, Kristin (2020). Glossa som forskningsverktøy. Hva folk søker etter og hva resultatene brukes til. Oslo Studies in Language (OSLa). 11(2), p. 449–464. doi: 10.5617/osla.8512. Full text in Research Archive Show summary

  Tekstlaboratoriets korpus og søkegrensesnittet Glossaer utviklatil bruk for språkforskere og andre interesserte fra hele Norden og resten av verden. I denne artikkelen viser vi hvordan søkesystemet Glossa er utviklafram mot i dag, hva korpusbrukerne søker på, og hvordan korpusdataene kan brukes i vitenskapelige publikasjoner.

• Fjeld, Ruth E. Vatvedt; Nøklestad, Anders & Hagen, Kristin (2020). Leksikografisk Bokmålskorpus (LBK) – Bakgrunn og bruk. In Johannessen, Janne Bondi & Hagen, Kristin (Ed.), Leksikografi og korpus. En hyllest til Ruth Vatvedt Fjeld. Universitetet i Oslo. ISSN 9788291398129. p. 101–124. doi: 10.5617/osla.8176. Full text in Research Archive Show summary

  Denne artikkelen er en introduksjon til Leksikografisk bokmålskorpus (LBK). Vi starter med en historisk oversikt over ordboksarbeid som er utført for norsk språk, og forklarer bakgrunnen for at LBK ble bygd opp på den måten det ble. Deretter gir vi en oversikt over innholdet i korpuset, før vi til slutt viser hvordan man kan søke i korpuset ved hjelp av korpussøkeverktøyet Glossa.

• Kåsen, Andre; Hagen, Kristin; Johannessen, Janne Bondi; Nøklestad, Anders & Priestley, Joel (2020). Comparing methods for measuring dialect similarity in 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 9791095546344. p. 5343–5350. Full text in Research Archive
• 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 9789179299958. p. 350–355. Full text in Research Archive Show summary

  This paper describes an evaluation of five data-driven part-of-speech (PoS) taggers for spoken Norwegian. The taggers all rely on different machine learning mechanisms: decision trees, hidden Markov models (HMMs), conditional random fields (CRFs), long-short term memory networks (LSTMs), and convolutional neural networks (CNNs). We go into some of the challenges posed by the task of tagging spoken, as opposed to written, language, and in particular a wide range of dialects as is found in the recordings of the LIA (Language Infrastructure made Accessible) project. The results show that the taggers based on either conditional random fields or neural networks perform much better than the rest, with the LSTM tagger getting the highest score.

• Lundquist, Bjørn; Larsson, Ida; Westendorp, Maud; Tengesdal, Eirik & Nøklestad, Anders (2019). Nordic Word Order Database: Motivations, methods, material and infrastructure. Nordic Atlas of Language Structures (NALS) Journal. 4(1), p. 1–33. doi: 10.5617/nals.7529. Full text in Research Archive Show summary

  In this article, we present the Nordic Word Order Database (NWD), with a focus on the rationale behind it, the methods used in data elicitation, data analysis and the empirical scope of the database. NWD is an online database with a user-friendly search interface, hosted by The Text Laboratory at the University of Oslo, launched in April 2019 (https://tekstlab.uio.no/nwd). It contains elicited production data from speakers of all of the North Germanic languages, including several different dialects. So far, 7 fieldtrips have been conducted, and data from altogether around 250 participants (age 16–60) have been collected (approx. 55 000 sentences in total). The data elicitation is carried out through a carefully controlled production experiment that targets core syntactic phenomena that are known to show variation within and/or between the North Germanic languages, e.g., subject placement, object placement, particle placement and verb placement. In this article, we present the motivations and research questions behind the database, as well as a description of the experiment, the data collection procedure, and the structure of the database.

• 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 9791095546009. p. 4482–4488. Full text in Research Archive Show summary

  This article presents the LIA treebank of transcribed spoken Norwegian dialects. It consists of dialect recordings made in the period between 1950--1990, which have been digitised, transcribed, and subsequently annotated with morphological and dependency-style syntactic analysis as part of the LIA (Language Infrastructure made Accessible) project at the University of Oslo. In this article, we describe the LIA material of dialect recordings and its transcription, transliteration and further morphosyntactic annotation. We focus in particular on the extension of the native NDT annotation scheme to spoken language phenomena, such as pauses and various types of disfluencies, and present the subsequent conversion of the treebank to the Universal Dependencies scheme. The treebank currently consists of 13,608 tokens, distributed over 1396 segments taken from three different dialects of spoken Norwegian. The LIA treebank annotation is an on-going effort and future releases will extend on the current data set.

• Nøklestad, Anders; Hagen, Kristin; Johannessen, Janne Bondi; Kosek, Michał & Priestley, Joel (2017). A modernised version of the Glossa corpus search system. In Tiedemann, Jörg (Eds.), Proceedings of the 21st Nordic Conference on Computational Linguistics (NoDaLiDa). Linköping University Electronic Press. ISSN 9789176856017. p. 251–254. Full text in Research Archive Show summary

  This paper presents and describes a modernised version of Glossa, a corpus search and results visualisation system with a user-friendly interface. The system is open source and can be easily installed on servers or even laptops for use with suitably prepared corpora. It handles parallel corpora as well as monolingual written and spoken corpora. For spoken corpora, the search results can be linked to audio/video, and spectrographic analysis and visualised geographical distributions can be provided. We will demonstrate the range of search options and result visualisations that Glossa provides.

• Kosek, Michał; Nøklestad, Anders; Priestley, Joel; Hagen, Kristin & Johannessen, Janne Bondi (2015). Visualisation in Speech Corpora: Maps and Waves in the Glossa System. In Grigonytė, Gintarė; Clematide, Simon; Utka, Andrius & Volk, Martin (Ed.), Proceedings of the Workshop on Innovative Corpus Query and Visualization Tools at NODALIDA 2015. Linköping University Electronic Press. ISSN 9789175190358. p. 23–31. Full text in Research Archive Show summary

  We present the Glossa web-based system for corpus search and results handling, focussing on two modes of visualisation implemented in the system. First, we describe the use of maps to show the geographical distribution of search results and its utility for exploring dialectal variation and discovering new isoglosses. Secondly, we present a functionality for speech visualisation, yielding dynamically generated representations of spectrograms, pitch and formants. The analyses are accompanied by the ability to replay selected parts of the waveform, as well as export and compare maximum, minimum and average values of the parameters for different selections. Among other things, this can be used to explore in more detail the set of spoken variants revealed by the geographical map view.

• Bick, Eckhard; Hagen, Kristin & Nøklestad, Anders (2015). Optimizing the Oslo-Bergen Tagger. In Bick, Eckhard & Hagen, Kristin (Ed.), Proceedings of the Workshop on “Constraint Grammar - methods, tools and applications” at NODALIDA 2015, May 11-13, 2015, Institute of the Lithuanian Language, Vilnius, Lithuania. Linköping University Electronic Press. ISSN 9789175190372. p. 11–17. Full text in Research Archive
• Kapociute-Dzikiene, Jurgita; Nøklestad, Anders; Johannessen, Janne Bondi & Krupavicius, Algis (2013). Exploring Features for Named Entity Recognition in Lithuanian Text Corpus. In Oepen, Stephan; Hagen, Kristin & Johannessen, Janne Bondi (Ed.), Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013). Linköping University Electronic Press. ISSN 9789175195896. p. 73–88. Full text in Research Archive Show summary

  Despite the existence of effective methods that solve named entity recognition tasks for such widely used languages as English, there is no clear answer which methods are the most suitable for languages that are substantially different. In this paper we attempt to solve a named entity recognition task for Lithuanian, using a supervised machine learning approach and exploring different sets of features in terms of orthographic and grammatical information, different windows, etc. Although the performance is significantly higher when language dependent features based on gazetteer lookup and automatic grammatical tools (part-of-speech tagger, lemmatizer or stemmer) are taken into account; we demonstrate that the performance does not degrade when features based on grammatical tools are replaced with affix information only. The best results (micro-averaged F-score=0.895) were obtained using all available features, but the results decreased by only 0.002 when features based on grammatical tools were omitted. Jurgita Kapociute-Dzikiene, Anders Nøklestad, Janne Bondi Johannessen, Algis Krupavicius (2013). Exploring Features for Named Entity Recognition in Lithuanian Text Corpus, Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013); May 22–24; 2013; Oslo University; Norway. NEALT Proceedings Series 16 http://www.ep.liu.se/ecp_article/index.en.aspx?issue=085;article=011

• Johannessen, Janne Bondi; Hagen, Kristin; Lynum, André & Nøklestad, Anders (2012). OBT-stat A combined rule-based and statistical tagger. In Andersen, Gisle (Eds.), Exploring newspaper language : using the web to create and investigate a large corpus of modern Norwegian. John Benjamins Publishing Company. ISSN 9789027203540. p. 51–65. doi: 10.1075/scl.49.03joh. Full text in Research Archive
• Johannessen, Janne Bondi; Priestley, Joel; Hagen, Kristin; Nøklestad, Anders & Lynum, Andre (2012). The Nordic Dialect Corpus. In Calzolari, Nicoletta; Choukri, Khalid; Declerck, Thierry; Dogan, Mehmet Ugur; Maegaard, Bente; Mariani, Joseph & Odijk, Jan (Ed.), Proceedings of the Eighth International Conference on Language Resources and Evaluation. European Language Resources Association. ISSN 9782951740877. p. 3388–3391. Full text in Research Archive Show summary

  In this paper, we describe the Nordic Dialect Corpus, which has recently been completed. The corpus has a variety of features that combined makes it an advanced tool for language researchers. These features include: Linguistic contents (dialects from five closely related languages), annotation (tagging and two types of transcription), search interface (advanced possibilities for combining a large array of search criteria and results presentation in an intuitive and simple interface), many search variables (linguistics-based, informant-based, time-based), multimedia display (linking of sound and video to transcriptions), display of results in maps, display of informant details (number of words and other information on informants), advanced results handling (concordances, collocations, counts and statistics shown in a variety of graphical modes, plus further processing). Finally, and importantly, the corpus is freely available for research on the web. We give examples of both various kinds of searches, of displays of results and of results handling. Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 3388-3391. Published with the permission of ELRA. This paper was published within the proceedings of the LREC 2008 and LREC 2012 Conferences. © 2008-2012 ELRA - European Language Resources Association. All rights reserved.

• Lynum, Andre; Hagen, Kristin; Johannessen, Janne Bondi & Nøklestad, Anders (2011). OBT+Stat: Evaluation of a combined CG and statistical tagger. NEALT Proceedings Series. ISSN 1736-8197. 14, p. 26–34. Full text in Research Archive
• Johannessen, Janne Bondi; Hagen, Kristin; Nøklestad, Anders & Priestley, Joel (2010). Enhancing Language Resources with Maps. 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 9782951740860. p. 1081–1088. Full text in Research Archive Show summary

  We will look at how maps can be integrated in research resources, such as language databases and language corpora. By using maps, search results can be illustrated in a way that immediately gives the user information that words or numbers on their own would not give. We will illustrate with two different resources, into which we have now added a Google Maps application: The Nordic Dialect Corpus (Johannessen et al. 2009) and The Nordic Syntactic Judgments Database (Lindstad et al. 2009). We have integrated Google Maps into these applications. The database contains some hundred syntactic test sentences that have been evaluated by four speakers in more than hundred locations in Norway and Sweden. Searching for the evaluations of a particular sentence gives a list of several hundred judgments, which are difficult for a human researcher to assess. With the map option, isoglosses are immediately visible. We show in the paper that both with the maps depicting corpus hits and with the maps depicting database results, the map visualizations actually show clear geographical differences that would be very difficult to spot just by reading concordance lines or database tables. Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), pages 1081-1088. Published with the permission of ELRA. This paper was published within the proceedings of the LREC 2008 and LREC 2012 Conferences. © 2008-2012 ELRA - European Language Resources Association. All rights reserved.

• Johannessen, Janne Bondi; Priestley, Joel & Nøklestad, Anders (2010). A MultilingualSpeech Resource: The Nordic Dialect Corpus. In Otoguro, Ryo; Ishikawa, Kiyoshi; Umemoto, Hiroshi; Yoshimoto, Kei & Harada, Yasunari (Ed.), Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation. Waseda University. ISSN 9784905166009. p. 749–758. Full text in Research Archive Show summary

  Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation, pages 749-758

• Hagen, Kristin & Nøklestad, Anders (2010). Bruk av et norsk leksikon til tagging og andre språkteknologiske formål. LexicoNordica. ISSN 0805-2735. p. 55–72. Full text in Research Archive
• Lindstad, Arne Martinus; Nøklestad, Anders; Johannessen, Janne Bondi & Vangsnes, Øystein Alexander (2009). The Nordic Dialect Database: Mapping Microsyntactic Variation in the Scandinavian Languages. NEALT Proceedings Series. ISSN 1736-8197. 4. Full text in Research Archive
• Søfteland, Åshild & Nøklestad, Anders (2008). "Manuell morfologisk tagging av NoTa-materialet med støtte fra en statistisk tagger". In Johannessen, Janne Bondi & Hagen, Kristin (Ed.), Språk i Oslo. Ny forskning omkring talespråk. Novus Forlag. ISSN 9788270994717. p. 226–234. Full text in Research Archive
• Johannessen, Janne Bondi; Nygaard, Lars; Priestley, Joel & Nøklestad, Anders (2008). Glossa: a Multilingual, Multimodal, Configurable User Interface. In Calzolari, Nicoletta (Eds.), Proceedings of the 6th International Conference on Language Resources and Evaluation. European Language Resources Association. ISSN 9782951740846. Full text in Research Archive Show summary

  We describe a web-based corpus query system, Glossa, which combines the expressiveness of regular query languages with the user-friendliness of a graphical interface. Since corpus users are usually linguists with little interest in technical matters, we have developed a system where the user need not have any prior knowledge of the search system. Furthermore, no previous knowledge of abbreviations for metavariables such as part of speech and source text is needed. All searches are done using checkboxes, pull-down menus, or writing simple letters to make words or other strings. Querying for more than one word is simply done by adding an additional query box, and for parts of words by choosing a feature such as "start of word". The Glossa system also allows a wide range of viewing and post-processing options. Collocations can be viewed and counted in a number of ways, and be viewed as different kinds of graphical charts. Further annotation and deletion of single results for further processing is also easy. The Glossa system is already in use for a number of corpora. Corpus administrators can easily adapt the system to a wide range of corpora, including multilingual corpora and corpora with audio and video content. Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), pages 617-622. Published with the permission of ELRA. This paper was published within the proceedings of the LREC 2008 and LREC 2012 Conferences. © 2008-2012 ELRA - European Language Resources Association. All rights reserved.

• Nøklestad, Anders & Søfteland, Åshild (2007). "Tagging a Norwegian speech corpus". In Nivre, Joakim; Kaalep, Heiki-Jaan; Muischnek, Kadri & Koit, Mare (Ed.), NODALIDA 2007 PROCEEDINGS. University of Tartu. ISSN 9789985405130. p. 245–248. Full text in Research Archive
• Johannessen, Janne Bondi; Hagen, Kristin; Haaland, Åsne; Nøklestad, Anders; Jónsdottir, Andra Björk & Kokkinakis, Dimitris [Show all 9 contributors for this article] (2005). Named Entity Recognition for the Mainland Scandinavian Languages. Literary & Linguistic Computing. ISSN 0268-1145. 20(1), p. 91–102. Full text in Research Archive
• Nøklestad, Anders (2005). Semi-unsupervised PP attachment disambiguation for Norwegian. Archives of Control Sciences. ISSN 0004-072X. 15(1), p. 385–396. Full text in Research Archive
• Nøklestad, Anders (2001). A Connectionist Model of Past Tense Acquisition in Norwegian, A Cognitive Approach to the Verb: Morphological and Constructional Perspectives. De Gruyter Mouton. ISSN 9783110170313. p. 165–187. Full text in Research Archive Show summary

  In cognitive linguistics theories and in connectionist models, both regular (or weak) and irregular (or strong) inflectional morphology are handled by the same kind of mechanism, a mechanism that is sensitive to the phonological form and the type and token frequencies of items in the linguistic input. In this paper I present a connectionist model of past tense acquisition in Norwegian and compare the model's behaviour to results from past tense elicitation experiments with Norwegian speakers. These comparisons, as well as investigations of the model's treatment of novel verbs, show that the model reflects many aspects of past tense inflection among Norwegian speakers, thus lending support to the single mechanism view on the acquisition and processing of inflectional morphology.

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• Nøklestad, Anders & Hagen, Kristin (2025). Glossa. doi: https:/www.hf.uio.no/iln/forskning/prosjekter/norchron/arrangementer/pdf/2kristin-hagen-og-anders-noklestad-oppstartseminar_norchron_kh_an.pdf. Full text in Research Archive
• Haug, Dag Trygve Truslew; Yildirim, Ahmet; Nøklestad, Anders & Kristen, Hagen (2023). Rules and neural nets for morphological tagging of Norwegian - Results and challenges. Full text in Research Archive
• Larsson, Ida; Lundquist, Bjørn; Westendorp, Maud; Nøklestad, Anders & Tengesdal, Eirik (2020). The Nordic Word Order Database. Full text in Research Archive
• Lundquist, Bjørn; Larsson, Ida; Westendorp, Maud; Tengesdal, Eirik & Nøklestad, Anders (2019). Presenting the Nordic Word Order Database. Full text in Research Archive
• Golden, Anne; Nøklestad, Anders & Johansson, Sofie (2019). The vocabulary of the Nordic heritage speakers in the US. An attempt of categorization. Full text in Research Archive
• Johannessen, Janne Bondi; Askeland, Anne Renette; Hagen, Kristin; Håberg, Live; Jensen, Bård Uri & Nøklestad, Anders [Show all 8 contributors for this article] (2018). Utfordringa med fonetisk transkripsjon av dialekter i den digitale tidsalderen: Oslo-translitteratoren. Full text in Research Archive
• Nøklestad, Anders; Hagen, Kristin; Johannessen, Janne Bondi; Kosek, Michał & Priestley, Joel (2017). A Modernised Version of the Glossa Corpus Search System. Full text in Research Archive
• Johannessen, Janne Bondi; Askeland, Anne Renette; Hagen, Kristin; Håberg, Live; Kristoffersen, Gjert & Nøklestad, Anders [Show all 9 contributors for this article] (2017). Hundre nye dialektordlister. Full text in Research Archive
• Søfteland, Åshild & Nøklestad, Anders (2016). Korpus-workshop. Full text in Research Archive
• Johannessen, Janne Bondi; Vangsnes, Øystein A; Lundquist, Bjørn; Larsson, Ida; Bentzen, Kristine & Garbacz, Piotr [Show all 10 contributors for this article] (2014). Nye isoglosser illustrert i det nye nettstedet for nordisk språk: NALS – Nordic Atlas of Language Structures (Online). Full text in Research Archive
• Priestley, Joel; Johannessen, Janne Bondi; Hagen, Kristin; Nøklestad, Anders & Lynum, André (2012). Maps as a central linguistic research tool. Full text in Research Archive
• Johannessen, Janne Bondi; Priestley, Joel; Hagen, Kristin; Nøklestad, Anders & Lynum, André (2012). The Nordic Dialect Corpus. Full text in Research Archive
• Nøklestad, Anders; Johannessen, Janne Bondi & Vangsnes, Øystein A (2011). The Nordic Syntactic Judgment Database:  informantvurderinger av syntaktiske konstruksjoner i skandinaviske dialek­ter. Full text in Research Archive
• Nøklestad, Anders (2010). Bruk av et norsk leksikon til tagging og andre språkteknologiske formål. Full text in Research Archive
• Johannessen, Janne Bondi; Hagen, Kristin; Nøklestad, Anders & Priestley, Joel (2010). Enhancing Language Resources with Maps. Full text in Research Archive
• Johannessen, Janne Bondi & Nøklestad, Anders (2010). Recent developments in the Nordic Dialect Corpus and the Nordic Syntactic Judgments Database. Full text in Research Archive
• Johannessen, Janne Bondi; Hagen, Kristin; Laake, Signe; Lindstad, Arne Martinus; Vangsnes, Øystein A. & Åfarli, Tor A. [Show all 7 contributors for this article] (2007). Dialektkorpus - presentasjon av prosjekt, metode, innsamling og materiale. Full text in Research Archive
• Johannessen, Janne Bondi; Nøklestad, Anders & Priestley, Joel (2007). Developing multi-Scandinavian word-lists for multi-Scandinavian texts. Full text in Research Archive
• Søfteland, Åshild & Nøklestad, Anders (2006). ”Manuell morfologisk tagging av NoTa-materialet med støtte fra en statistisk tagger”. Full text in Research Archive
• Nøklestad, Anders (2005). Memory-based PP Attachment Disambiguation for Norwegian. Full text in Research Archive
• Samdal, Gunn Inger Lyse & Nøklestad, Anders (2005). A distributional or a translational basis for data-driven sense discrimination? Full text in Research Archive
• Nøklestad, Anders; Johansson, Christer & Bosch, Antal van den (2004). Pronominal anaphora resolution in Norwegian using TiMBL and z-scores. Full text in Research Archive
• Nøklestad, Anders (2004). Memory-based Classification of Proper Names in Norwegian. Full text in Research Archive
• Johannessen, Janne Bondi; Nøklestad, Anders; Hagen, Kristin & Lindstad, Arne Martinus (2000). Det åpne laboratoriet. [Journal]. Apollon. Full text in Research Archive
• Hagen, Kristin; Nøklestad, Anders & Johannessen, Janne Bondi (2000). A Constraint-based Tagger for Norwegian. Full text in Research Archive Show summary

  Disambiguating morphosyntactic taggers are computer programs which provide the words in a text with grammatical information and which are able to pick the correct reading for ambiguous words based on linguistic context. We describe such a tagger for Norwegian BOKMÅL and NYNORSK which is based on the Constraint Grammar formalism (Karlsson et al. 1995). The tagger disambiguates through the use of linguistic constraints that operate only the level of individual words, which means that no phrase structure is established. We show how it is possible to perform morphological and syntactic disambiguation of Norwegian texts without having recourse to a phrasal level.

• Johannessen, Janne Bondi & Nøklestad, Anders (2000). Oslo-korpuset av taggede, norske tekster. Full text in Research Archive
• Johannessen, Janne Bondi & Nøklestad, Anders (2000). Oslo-korpuset av taggede, norske tekster. Full text in Research Archive
• Johannessen, Janne Bondi & Nøklestad, Anders (2000). Mot et maksimalt brukervennlig korpus. Full text in Research Archive
• Johannessen, Janne Bondi; Nøklestad, Anders & Hagen, Kristin (2000). A Web-Based Advanced and User Friendly System: The Oslo Corpus of Tagged Norwegian Texts. Full text in Research Archive Show summary

  A general purpose text corpus meant for linguists and lexicographers needs to satify quality criteria at at least four different levels. The first two criteria are fairly well established; the corpus should have a wide variety of texts and be tagged according to a fine-grained system. The last two criteria are much less widely appreciated, unfortunately. One has to do with variety of search criteria: the user should be allowed to search for any information contained in the corpus, and with any combination possible. In addition, the search results should be presented in a choice of ways. The forth criterion has to do with accessability. It is a rather surprising fact that while user interfaces tend to be simple and self explanatory in most areas of life represented electronically, corpus interfaces are still extremely user unfriendly. In this paper, we present a corpus whose interface we have given a lot of thought, and likewise the possible search options, viz. the Oslo Corpus of Tagged Norwegian Texts.

• Johannessen, Janne Bondi; Nøklestad, Anders & Hagen, Kristin (2000). A Web-Based Advanced and User Friendly System: The Oslo Corpus of Tagged Norwegian Texts. Full text in Research Archive Show summary

  A general purpose text corpus meant for linguists and lexicographers needs to satify quality criteria at at least four different levels. The first two criteria are fairly well established; the corpus should have a wide variety of texts and be tagged according to a fine-grained system. The last two criteria are much less widely appreciated, unfortunately. One has to do with variety of search criteria: the user should be allowed to search for any information contained in the corpus, and with any combination possible. In addition, the search results should be presented in a choice of ways. The forth criterion has to do with accessability. It is a rather surprising fact that while user interfaces tend to be simple and self explanatory in most areas of life represented electronically, corpus interfaces are still extremely user unfriendly. In this paper, we present a corpus whose interface we have given a lot of thought, and likewise the possible search options, viz. the Oslo Corpus of Tagged Norwegian Texts.

• Hagen, Kristin; Johannessen, Janne Bondi & Nøklestad, Anders (1999). The shortcomings of a tagger. Full text in Research Archive Show summary

  The tagger used for the Oslo Corpus of Tagged Norwegian Texts has very good statistical results. In spite of this, it makes mistakes. In this paper we take a closer look at some of them. Although some mistakes are of a kind that would disappear if we improved the tagger, many are impossible or very difficult to do anything about. They are due to errors in the corpus (spelling errors, foreign words, non-standard spellings), to elliptic sentences, such as headlines, and to structural ambiguity, which abounds to a surprising extent. Proofreading the corpus would have removed the first kind of problems, but the other two types cannot be resolved in any obvious way.

• Johannessen, Janne Bondi & Nøklestad, Anders (1999). Tavle-analyse ut - data-analyse inn. [Journal]. Aftenposten. Full text in Research Archive
• Nøklestad, Anders (2009). A Machine Learning Approach to Anaphora Resolution Including Named Entity Recognition, PP Attachment Disambiguation, and Animacy Detection. Universitetet i Oslo. Full text in Research Archive Show summary

  Avhandlingen beskriver et automatisk anaforløsningssystem (AL-system) for norsk med fokus på pronominale anaforer i skjønnlitterære tekster. Systemet bygger primært på maskinlæringsmetoder og er det første norske AL-systemet som bruker maskinlæring. Et sett av lingvistisk funderte filtre fjerner inkompatible antecedentkandidater før de resterende kandidatene klassifiseres enten som antecedenter eller ikke-antecedenter. Den nærmeste kandidaten som klassifiseres som passende antecedent (hvis en slik finnes), velges som antecedent for pronomenet.<br><br> Tre ulike maskinlæringsmetoder for klassifisering blir evaluert og sammenliknet: minnebasert læring (MBL), maksimum entropi-modellering (MaksEnt) og støttevektormaskiner (SVMer). Metodene blir testet både med standard parameterverdier og med automatisk optimiserte verdier. Ulike pronomen håndteres av ulike klassifikatorer. To andre kunnskapsfattige tilnærminger, en faktor/indikator-basert tilnærming og en som er basert på Centering Theory, blir sammenliknet med maskinlæringsmetodene. De beste maskinlæringsmetodene fungerer signifikant bedre enn tilnærmingene som ikke er basert på maskinlæring og signifikant bedre enn det eneste eksisterende AL-systemet for norsk.<br><br> Avhandlingen beskriver også utvikling og evaluering av tre støttemoduler som bidrar med informasjon til AL-systemet: en navnetypegjenkjenner, en PP-tilordner og en animathetsdetektor. Ulike maskinlæringsmetoder blir testet og sammenliknet med hensyn til hvor godt de fungerer for de to første modulene. PP-tilordneren er basert på en nyskapende form for halvovervåket læring, mens animathetsdetektoren bruker to ulike metoder for å hente ut animathetsinformasjon for substantiver fra Internett. De tre støttemodulene evalueres både som selvstendige NLP-verktøy og som informasjonskilder for AL-systemet.<br><br> I nesten alle eksperimentene som er beskrevet i avhandlingen, fungerer MBL like godt eller bedre enn MaksEnt, mens prestasjonsnivået til SVMene er signifikant dårligere.

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