BibTeX

@inProceedings{grand-clement-masciolini-2026-sharing-364244,
	title        = {Sharing is Caring: Advantages of Sharing a Language Background with Learners as an Annotator of Learner Data in UD},
	abstract     = {This paper looks at the impact of annotators sharing a language background with learners when annotating learner data using the Universal Dependencies (UD) framework. We perform a study comparing annotations by two different annotators working on sets of L2 Swedish sentences (learner sentences and target corrections) from the Swedish Learner Language corpus (SweLL) written by learners for whom French is a main writing language. The annotators are both L2 speakers of Swedish but have different knowledge of French: one is a native French speaker and the other has no knowledge of French. We find high annotator agreement, which may indicate an non-significant impact, though we qualitatively observe an advantage in sharing language background.},
	booktitle    = {Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026)},
	author       = {Grand-Clement, Caroline and Masciolini, Arianna},
	year         = {2026},
	publisher    = {Association for Computational Linguistics},
	address      = {San Diego, California, USA},
	pages        = {503–512},
}

@inProceedings{klironomou-etal-2026-towards-364219,
	title        = {Towards Universal Dependencies for L2 learners of modern Greek: Annotation and challenges},
	abstract     = {This paper focuses on annotating the Greek Learner Corpus in Universal Dependencies (UD). It presents the annotation process, development of guidelines and evaluation of the attempted annotation of two annotators. This work is part of a larger annotation project which aims to compile a sizeable learner treebank that can be used to promote research on second language acquisition and its automatic processing.},
	booktitle    = {Proceedings of the ninth workshop on Universal Dependencies (UDW, LREC 2026)},
	author       = {Klironomou, Christina and Pasparaki, Thelka and Masciolini, Arianna and Tantos, Alexandros and Touriki, Despoina-Ourania and Tsiotskas, Konstantinos and Tsourilla, Eleni},
	year         = {2026},
}

@inProceedings{deworetzki-masciolini-2026-syntactic-364221,
	title        = {Syntactic Sugar for Syntactic Queries: Sequential Representations for Dependency Queries},
	abstract     = {Syntactic query languages such as Grew and dep_search allow looking for grammatical patterns in linguistically annotated corpora. However, these languages are often unsupported by large-scale corpus management tools, where queries are of an essentially sequential nature. In this paper, we present CQP/Tree, a tool to convert syntactic queries into CQL, the Corpus Query Language used in Corpus Workbench, SketchEngine, Korp and several other such systems. In this framework, syntactic queries act as _syntactic sugar_: they allow expressing complex CQL queries in a more readable and concise fashion, thus bridging the gap between expressive linguistic search and large-scale corpora. CQP/Tree is available as a web and command-line tool, as well as an open source Python library.},
	booktitle    = {Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)},
	author       = {Deworetzki, Niklas and Masciolini, Arianna},
	year         = {2026},
	publisher    = {European Language Resources Association (ELRA)},
	address      = {Palma, Mallorca, Spain},
	pages        = {11669----11678},
}
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