EKAW 2024, 24th International Conference on Knowledge Engineering and Knowledge Management, Poster and Demo Track, 26-28 November 2024, Amsterdam, The Netherlands
Event relation extraction is crucial for understanding the temporal sequence and interconnections between events. To demonstrate this, we developed a Streamlit-based application that showcases our event relation extraction system, capable of identifying semantically accurate relations such as Direct-cause, Enable, Intend, and Prevent. The
system features an API that simplifies inference and displays results in a user-friendly manner. Users can input text like a sentence and the application highlights extracted events and their corresponding relationships. The backend runs a series of pre-trained language models, trained on datasets focused on events and their semantic relations.
The app allows users to switch between various models, including HuggingFace’s RoBERTa, REBEL, and large language models like Zephyr. The demo is available at https://demo.kflow.eurecom.fr/.
Type:
Poster / Demo
City:
Amsterdam
Date:
2024-11-26
Department:
Data Science
Eurecom Ref:
8052
See also: