Search Results for author: Juhani Luotolahti

Found 13 papers, 1 papers with code

From Web Crawl to Clean Register-Annotated Corpora

no code implementations • LREC 2020 • Veronika Laippala, Samuel R{\"o}nnqvist, Saara Hellstr{\"o}m, Juhani Luotolahti, Liina Repo, Anna Salmela, Valtteri Skantsi, Sampo Pyysalo

However, two critical steps in the development of web corpora remain challenging: the identification of clean text from source HTML and the assignment of genre or register information to the documents.

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Multilingual is not enough: BERT for Finnish

1 code implementation • 15 Dec 2019 • Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, Juhani Luotolahti, Tapio Salakoski, Filip Ginter, Sampo Pyysalo

Deep learning-based language models pretrained on large unannotated text corpora have been demonstrated to allow efficient transfer learning for natural language processing, with recent approaches such as the transformer-based BERT model advancing the state of the art across a variety of tasks.

Dependency Parsing named-entity-recognition +4

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Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks v2.0

no code implementations • WS 2017 • Juhani Luotolahti, Jenna Kanerva, Filip Ginter

In this paper we present our system in the DiscoMT 2017 Shared Task on Crosslingual Pronoun Prediction.

Machine Translation Word Embeddings

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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

no code implementations • CONLL 2017 • Daniel Zeman, Martin Popel, Milan Straka, Jan Haji{\v{c}}, Joakim Nivre, Filip Ginter, Juhani Luotolahti, Sampo Pyysalo, Slav Petrov, Martin Potthast, Francis Tyers, Elena Badmaeva, Memduh Gokirmak, Anna Nedoluzhko, Silvie Cinkov{\'a}, Jan Haji{\v{c}} jr., Jaroslava Hlav{\'a}{\v{c}}ov{\'a}, V{\'a}clava Kettnerov{\'a}, Zde{\v{n}}ka Ure{\v{s}}ov{\'a}, Jenna Kanerva, Stina Ojala, Anna Missil{\"a}, Christopher D. Manning, Sebastian Schuster, Siva Reddy, Dima Taji, Nizar Habash, Herman Leung, Marie-Catherine de Marneffe, Manuela Sanguinetti, Maria Simi, Hiroshi Kanayama, Valeria de Paiva, Kira Droganova, H{\'e}ctor Mart{\'\i}nez Alonso, {\c{C}}a{\u{g}}r{\i} {\c{C}}{\"o}ltekin, Umut Sulubacak, Hans Uszkoreit, Vivien Macketanz, Aljoscha Burchardt, Kim Harris, Katrin Marheinecke, Georg Rehm, Tolga Kayadelen, Mohammed Attia, Ali Elkahky, Zhuoran Yu, Emily Pitler, Saran Lertpradit, M, Michael l, Jesse Kirchner, Hector Fern Alcalde, ez, Jana Strnadov{\'a}, Esha Banerjee, Ruli Manurung, Antonio Stella, Atsuko Shimada, Sookyoung Kwak, Gustavo Mendon{\c{c}}a, L, Tatiana o, Rattima Nitisaroj, Josie Li

The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets.

Dependency Parsing