Papers by Teresa Paccosi

2 papers
Building a Multilingual Taxonomy of Olfactory Terms with Timestamps (2022.lrec-1)

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Challenge: olfactory references play a crucial role in our memory and experiences . but only few works in NLP have attempted to capture this sensory dimension from a computational perspective.
Approach: They describe a process that has led to the semi-automatic development of a taxonomy for olfactory information in four languages (English, French, German and Italian)
Outcome: The proposed taxonomy can be extended using existing language models and n-grams to include olfactory terms in four languages.
KIND: an Italian Multi-Domain Dataset for Named Entity Recognition (2022.lrec-1)

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Challenge: Named-entity recognition is a task that uses named entities to classify texts . annotated data are time and money consuming, since they need to be created by experts of the domain of the annotation that is going to be done .
Approach: They present an Italian dataset for Named-entity recognition with manual annotations and a semi-automatically annotated part.
Outcome: The proposed dataset covers different styles and language uses, and is the largest in Italy.

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