Search Results for author:
Found 5 papers, 1 papers with code
Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models
Temporal knowledge graph question answering (TKGQA) poses a significant challenge task, due to the temporal constraints hidden in questions and the answers sought from dynamic structured knowledge.
A Unified Generative Framework based on Prompt Learning for Various Information Extraction Tasks
In this paper, we propose a novel composable prompt-based generative framework, which could be applied to a wide range of tasks in the field of Information Extraction.
P-ADMMiRNN: Training RNN with Stable Convergence via An Efficient and Paralleled ADMM Approach
We also provide novel update rules and theoretical convergence analysis.
Event Arguments Extraction via Dilate Gated Convolutional Neural Network with Enhanced Local Features
However, the F-Score of event arguments extraction is much lower than that of event trigger extraction, i. e. in the most recent work, event trigger extraction achieves 80. 7%, while event arguments extraction achieves only 58%.
Exploring Pre-trained Language Models for Event Extraction and Generation
Traditional approaches to the task of ACE event extraction usually depend on manually annotated data, which is often laborious to create and limited in size.
