Text2Event: Controllable sequence-to-structure generation for end-to-end event extraction
Event extraction is challenging due to the complex structure of event records and the
semantic gap between text and event. Traditional methods usually extract event records by …
semantic gap between text and event. Traditional methods usually extract event records by …
DEGREE: A data-efficient generation-based event extraction model
Event extraction requires high-quality expert human annotations, which are usually
expensive. Therefore, learning a data-efficient event extraction model that can be trained …
expensive. Therefore, learning a data-efficient event extraction model that can be trained …
Event extraction as multi-turn question answering
Event extraction, which aims to identify event triggers of pre-defined event types and their
arguments of specific roles, is a challenging task in NLP. Most traditional approaches …
arguments of specific roles, is a challenging task in NLP. Most traditional approaches …
Dynamic prefix-tuning for generative template-based event extraction
We consider event extraction in a generative manner with template-based conditional
generation. Although there is a rising trend of casting the task of event extraction as a …
generation. Although there is a rising trend of casting the task of event extraction as a …
A survey on deep learning event extraction: Approaches and applications
Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …
from massive textual data. With the rapid development of deep learning, EE based on deep …
OneEE: A one-stage framework for fast overlapping and nested event extraction
Event extraction (EE) is an essential task of information extraction, which aims to extract
structured event information from unstructured text. Most prior work focuses on extracting flat …
structured event information from unstructured text. Most prior work focuses on extracting flat …
Event detection: Gate diversity and syntactic importance scoresfor graph convolution neural networks
Recent studies on event detection (ED) haveshown that the syntactic dependency graph
canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per …
canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per …
Meta-learning with dynamic-memory-based prototypical network for few-shot event detection
Event detection (ED), a sub-task of event extraction, involves identifying triggers and
categorizing event mentions. Existing methods primarily rely upon supervised learning and …
categorizing event mentions. Existing methods primarily rely upon supervised learning and …
Document-level event extraction via heterogeneous graph-based interaction model with a tracker
Document-level event extraction aims to recognize event information from a whole piece of
article. Existing methods are not effective due to two challenges of this task: a) the target …
article. Existing methods are not effective due to two challenges of this task: a) the target …
An overview of event extraction and its applications
J Liu, L Min, X Huang - arXiv preprint arXiv:2111.03212, 2021 - arxiv.org
With the rapid development of information technology, online platforms have produced
enormous text resources. As a particular form of Information Extraction (IE), Event Extraction …
enormous text resources. As a particular form of Information Extraction (IE), Event Extraction …