Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Pilan, Ildiko"'
Text sanitization is the task of redacting a document to mask all occurrences of (direct or indirect) personal identifiers, with the goal of concealing the identity of the individual(s) referred in it. In this paper, we consider a two-step approach t
Externí odkaz:
http://arxiv.org/abs/2310.14312
Publikováno v:
In Proceedings of SIGdial 2024, pp. 440-457. Kyoto, Japan (2024)
Scripted dialogues such as movie and TV subtitles constitute a widespread source of training data for conversational NLP models. However, there are notable linguistic differences between these dialogues and spontaneous interactions, especially regard
Externí odkaz:
http://arxiv.org/abs/2309.15656
We propose a novel method to bootstrap text anonymization models based on distant supervision. Instead of requiring manually labeled training data, the approach relies on a knowledge graph expressing the background information assumed to be publicly
Externí odkaz:
http://arxiv.org/abs/2205.06895
Autor:
Pilán, Ildikó, Lison, Pierre, Øvrelid, Lilja, Papadopoulou, Anthi, Sánchez, David, Batet, Montserrat
We present a novel benchmark and associated evaluation metrics for assessing the performance of text anonymization methods. Text anonymization, defined as the task of editing a text document to prevent the disclosure of personal information, currentl
Externí odkaz:
http://arxiv.org/abs/2202.00443
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, including automatically mapped terms from a Norwegian medical dictionar
Externí odkaz:
http://arxiv.org/abs/2004.02509
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 system combining heuristics and machine learning methods includes a nu
Externí odkaz:
http://arxiv.org/abs/1706.03530
Autor:
Pilán, Ildikó
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 exercises from corpora which are presentable in isolation. An in-depth
Externí odkaz:
http://arxiv.org/abs/1605.01845
Autor:
Volodina, Elena, Pilán, Ildikó, Enström, Ingegerd, Llozhi, Lorena, Lundkvist, Peter, Sundberg, Gunlög, Sandell, Monica
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). SweLL consists of three subcorpora - SpIn, SW1203 and Tisus, collected fr
Externí odkaz:
http://arxiv.org/abs/1604.06583
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 level. In this paper, we aim at addressing this issue by presenting the
Externí odkaz:
http://arxiv.org/abs/1603.08868
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