activity
20162020
most citedCandidate sentence selection for language learning exercises: from a comprehensive framework to an empirical evaluation

20 citations · 20 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2020

Building a Norwegian Lexical Resource for Medical Entity Recognition

Ildikó Pilán, Pål H. Brekke, Lilja Øvrelid

We present a large Norwegian lexical resource of categorized medical terms. The resource merges information from large medical databases, and contains over 77,000 unique entries, i…

cs.CL201720 cited

Candidate sentence selection for language learning exercises: from a comprehensive framework to an empirical evaluation

Ildikó Pilán, Elena Volodina, Lars Borin

We present a framework and its implementation relying on Natural Language Processing methods, which aims at the identification of exercise item candidates from corpora. The hybrid…

cs.CL2016

Detecting Context Dependence in Exercise Item Candidates Selected from Corpora

Ildikó Pilán

We explore the factors influencing the dependence of single sentences on their larger textual context in order to automatically identify candidate sentences for language learning e…

cs.CL2016

SweLL on the rise: Swedish Learner Language corpus for European Reference Level studies

Elena Volodina, Ildikó Pilán, Ingegerd Enström +4

We present a new resource for Swedish, SweLL, a corpus of Swedish Learner essays linked to learners' performance according to the Common European Framework of Reference (CEFR). Swe…

cs.CL2016

A Readable Read: Automatic Assessment of Language Learning Materials based on Linguistic Complexity

Ildikó Pilán, Sowmya Vajjala, Elena Volodina

Corpora and web texts can become a rich language learning resource if we have a means of assessing whether they are linguistically appropriate for learners at a given proficiency l…