In this paper, we introduce an innovative approach where we employ large language models (LLMs) as expert annotators for event extraction. We strategically ...

In this paper, leveraging Large Language Models (LLMs), we propose novel methods for event extraction and generation based on dialogues.

Extracting events from unstructured text aims to answer the who, what, when, where, why, and how questions about an occurrence in a structured manner.

By utilizing LLMs to identify and correct errors of SLMs predictions based on automatically generated feedback information, EE performances can be improved ...

Event Extraction (EE) is a fundamental task in information extraction, aimed at identifying events and their associated arguments within textual data.

EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models, Arxiv, 2024-02 ; Guideline Learning for In-context Information Extraction ...

31 окт. 2024 г. · Our project at the Biomedical Linked Annotation Hackathon 8 (BLAH 8) investigates the feasibility of using LLMs to extract biological regulation events.

29 мая 2024 г. · Event extraction aims at identifying and categorizing events described within a text, including the recognition of the entities involved in the ...

10 авг. 2024 г. · Event extraction identifies events and their core elements from unstructured text data, detailing participants ("who"), time ("when"), location ...

8 июн. 2024 г. · If anyone can give me some ideas to do the same or suggest me some good LLM models that can perform Extractive QA and Text classification.