BibTeX

@inProceedings{masciolini-toth-2024-stund-335974,
	title        = {STUnD: ett Sökverktyg för Tvåspråkiga Universal Dependencies-trädbanker },
	abstract     = {Föreliggande artikel introducerar STUND, ett Sökverktyg för Tvåspråkiga Universal Dependencies-trädbanker som möjliggör parallella syntaktiska sökningar. Vi demonstrerar dess praktiska tillämpning i en fallstudie på tempusformen presens perfekt i svenska och engelska. Resultaten visar att presens perfekt används i ungefär lika stor utsträckning i båda språken, men att det förekommer viss variation som verkar bero på språkspecifika konventioner och översättningsstrategier. },
	booktitle    = {Proceedings of the Huminfra Conference (HiC 2024) },
	author       = {Masciolini, Arianna and Tóth, Márton András},
	year         = {2024},
	ISBN         = {978-91-8075-512-2},
}

@inProceedings{masciolini-etal-2023-towards-329384,
	title        = {Towards automatically extracting morphosyntactical error patterns from L1-L2 parallel dependency treebanks},
	abstract     = {L1-L2 parallel dependency treebanks are UD-annotated corpora of learner sentences paired with correction hypotheses. Automatic morphosyntactical annotation has the potential to remove the need for explicit manual error tagging and improve interoperability, but makes it more challenging to locate grammatical errors in the resulting datasets. We therefore propose a novel method for automatically extracting morphosyntactical error patterns and perform a preliminary bilingual evaluation of its first implementation through a similar example retrieval task. The resulting pipeline is also available as a prototype CALL application.},
	booktitle    = {Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), July 13, 2023, Toronto, Canada},
	author       = {Masciolini, Arianna and Volodina, Elena and Dannélls, Dana},
	year         = {2023},
	publisher    = {Association for Computational Linguistics},
	address      = {Stroudsburg, PA},
	ISBN         = {978-1-959429-80-7},
}

@inProceedings{masciolini-2023-query-329383,
	title        = {A query engine for L1-L2 parallel dependency treebanks},
	abstract     = {L1-L2 parallel dependency treebanks are learner corpora with interoperability as their main design goal. They consist of sentences produced by learners of a second language (L2) paired with native-like (L1) correction hypotheses. Rather than explicitly labelled for errors, these are annotated following the Universal Dependencies standard. This implies relying on tree queries for error retrieval. Work in this direction is, however, limited. We present a query engine for L1-L2 treebanks and evaluate it on two corpora, one manually validated and one automatically parsed.},
	booktitle    = {Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), May 22-24, 2023 Tórshavn, Faroe Islands  / Editors: Tanel Alumäe and Mark Fishel},
	author       = {Masciolini, Arianna},
	year         = {2023},
	publisher    = {University of Tartu Library},
	address      = {Tartu, Estonia},
	ISBN         = {978-99-1621-999-7},
}

@inProceedings{masciolini-ranta-2021-grammar-324794,
	title        = {Grammar-based concept alignment for domain-specific Machine Translation},
	abstract     = {Grammar-based domain-specific MT systems are a common use case for CNLs. High-quality translation lexica are a crucial part of such systems, but involve time consuming work and significant linguistic knowledge. With parallel example sentences available, statistical alignment tools can help automate part of the process, but they are not suitable for small datasets and do not always perform well with complex multiword expressions. In addition, the correspondences between word forms obtained in this way cannot be used directly. Addressing these problems, we propose a grammar-based approach to this task and put it to test in a simple translation pipeline.},
	booktitle    = {Proceedings of the Seventh International Workshop on Controlled Natural Language (CNL 2020/21)},
	author       = {Masciolini, Arianna and Ranta, Aarne},
	year         = {2021},
}