We present the system proposed by the MilaNLP team for the Explainable Detection of Online Sexism (EDOS) shared task. We propose an ensemble modeling approach to combine different classifiers trained with domain adaptation objectives and standard …
The task of Named Entity Recognition (NER) is aimed at identifying named entities in a given text and classifying them into pre-defined domain entity types such as persons, organizations, locations. Most of the existing NER systems make use of …
Given the potential rise in the amount of user-generated content on social network, research efforts towards Information Extraction have significantly increased, giving leeway to the emergence of numerous *Named Entity Recognition* (NER) systems. …
Numerous state-of-the-art **Named Entity Recognition** (NER) systems use different classification schemas/ontologies. Comparisons and integration among NER systems, thus, becomes complex. In this paper, we propose a transfer-learning approach where …
Real world applications of machine learning in natural language processing can span many different domains and usually require a huge effort for the annotation of domain specific training data. For this reason, domain adaptation techniques have …