Papers by Borbála Novák
NerKor+Cars-OntoNotes++ (2022.lrec-1)
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| Challenge: | In this paper, we present an upgraded version of the Hungarian NYTK-NerKor named entity corpus . it contains twice as many annotated spans and 7 times as many distinct entity types as the original version. |
| Approach: | They present an upgraded version of the Hungarian NYTK-NerKor named entity corpus with an extended OntoNotes 5 annotation scheme. |
| Outcome: | The enhanced version of the corpus contains twice as many annotated spans and 7 times more distinct entity types than the original version. |
CBOW-tag: a Modified CBOW Algorithm for Generating Embedding Models from Annotated Corpora (2020.lrec-1)
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| Challenge: | Using word2vec, we train distributional semantic models that predict a word from the context or vice versa. |
| Approach: | They propose a modified version of the CBOW algorithm implemented in the fastText framework that includes the representation of original word forms and their annotation at the same time. |
| Outcome: | The proposed model can answer questions such as What do we eat?, What can we do with a skeleton?, etc. |
Cross-Lingual Generation and Evaluation of a Wide-Coverage Lexical Semantic Resource (L18-1)
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| Challenge: | Neural word embedding models are not interpretable for humans by themselves . we present a method that assigns explicit symbolic semantic features to words . |
| Approach: | They propose a method that assigns explicit symbolic semantic features to words in an embedding model . they use a finite list of terms to make the model interpretable for humans . |
| Outcome: | The proposed method is shown to be very efficient for word embedding models . it can be applied across languages and can be used as a searchable semantic annotation . |