Aspect-based sentiment analysis (ABSA) is a natural language processing technique that
seeks to recognize and extract the sentiment connected to various qualities or aspects of a …

We present Mask-then-Fill, a flexible and effective data augmentation framework for event
extraction. Our approach allows for more flexible manipulation of text and thus can generate …

Event argument extraction (EAE) aims to identify the arguments of a given event, and
classify the roles that those arguments play. Due to high data demands of training EAE …

Extracting the reported events from text is one of the key research themes in natural
language processing. This process includes several tasks such as event detection …

Cross-lingual transfer-learning is widely used in Event Extraction for low-resource
languages and involves a Multilingual Language Model that is trained in a source language …

Document-level event extraction is a long-standing challenging information retrieval
problem involving a sequence of sub-tasks: entity extraction, event type judgment, and event …

The extraction of essential news elements through the 5W1H framework (What, When,
Where, Why, Who, and How) is critical for event extraction and text summarization. The …

Event extraction, grounded in semantic relationships, can serve as a simplified relation
extraction. In this study, we propose an efficient open-domain event annotation framework …

Event extraction (EE) is crucial to downstream tasks such as new aggregation and event
knowledge graph construction. Most existing EE datasets manually define fixed event types …

In this study, we demonstrate how to apply cross-lingual annotation projection to transfer
named-entity annotations to classical languages for which limited or no resources and …