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Found 15 papers, 3 papers with code
Open Dutch WordNet
We describe Open Dutch WordNet, which has been derived from the Cornetto database, the Princeton WordNet and open source resources.
More is not always better: balancing sense distributions for all-words Word Sense Disambiguation
Current Word Sense Disambiguation systems show an extremely poor performance on low frequent senses, which is mainly caused by the difference in sense distributions between training and test data.
Word Sense Disambiguation with LSTM: Do We Really Need 100 Billion Words?
Recently, Yuan et al. (2016) have shown the effectiveness of using Long Short-Term Memory (LSTM) for performing Word Sense Disambiguation (WSD).
SemEval-2018 Task 5: Counting Events and Participants in the Long Tail
This paper discusses SemEval-2018 Task 5: a referential quantification task of counting events and participants in local, long-tail news documents with high ambiguity.
A Deep Dive into Word Sense Disambiguation with LSTM
LSTM-based language models have been shown effective in Word Sense Disambiguation (WSD).
Semantic overfitting: what `world' do we consider when evaluating disambiguation of text?
Semantic text processing faces the challenge of defining the relation between lexical expressions and the world to which they make reference within a period of time.
Addressing the MFS Bias in WSD systems
Word Sense Disambiguation (WSD) systems tend to have a strong bias towards assigning the Most Frequent Sense (MFS), which results in high performance on the MFS but in a very low performance on the less frequent senses.
Combining Conceptual and Referential Annotation to Study Variation in Framing
The user can apply two types of annotations: 1) mappings from expressions to frames and frame elements, 2) reference relations from mentions to events and participants of the structured data.
Large-scale Cross-lingual Language Resources for Referencing and Framing
In this article, we lay out the basic ideas and principles of the project Framing Situations in the Dutch Language.
Variation in framing as a function of temporal reporting distance
In this paper, we measure variation in framing as a function of foregrounding and backgrounding in a co-referential corpus with a range of temporal distance.
