A metaverse: Taxonomy, components, applications, and open challenges

SM Park, YG Kim - IEEE access, 2022 - ieeexplore.ieee.org
Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …

A frustratingly easy approach for entity and relation extraction

Z Zhong, D Chen - arXiv preprint arXiv:2010.12812, 2020 - arxiv.org
End-to-end relation extraction aims to identify named entities and extract relations between
them. Most recent work models these two subtasks jointly, either by casting them in one …

Span-based joint entity and relation extraction with transformer pre-training

M Eberts, A Ulges - ECAI 2020, 2020 - ebooks.iospress.nl
We introduce SpERT, an attention model for span-based joint entity and relation extraction.
Our key contribution is a light-weight reasoning on BERT embeddings, which features entity …

Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction

Y Luan, L He, M Ostendorf, H Hajishirzi - arXiv preprint arXiv:1808.09602, 2018 - arxiv.org
We introduce a multi-task setup of identifying and classifying entities, relations, and
coreference clusters in scientific articles. We create SciERC, a dataset that includes …

Onerel: Joint entity and relation extraction with one module in one step

YM Shang, H Huang, X Mao - Proceedings of the AAAI conference on …, 2022 - ojs.aaai.org
Joint entity and relation extraction is an essential task in natural language processing and
knowledge graph construction. Existing approaches usually decompose the joint extraction …

Entity-relation extraction as multi-turn question answering

X Li, F Yin, Z Sun, X Li, A Yuan, D Chai… - arXiv preprint arXiv …, 2019 - arxiv.org
In this paper, we propose a new paradigm for the task of entity-relation extraction. We cast
the task as a multi-turn question answering problem, ie, the extraction of entities and …

Extracting relational facts by an end-to-end neural model with copy mechanism

X Zeng, D Zeng, S He, K Liu, J Zhao - Proceedings of the 56th …, 2018 - aclanthology.org
The relational facts in sentences are often complicated. Different relational triplets may have
overlaps in a sentence. We divided the sentences into three types according to triplet …

A general framework for information extraction using dynamic span graphs

Y Luan, D Wadden, L He, A Shah, M Ostendorf… - arXiv preprint arXiv …, 2019 - arxiv.org
We introduce a general framework for several information extraction tasks that share span
representations using dynamically constructed span graphs. The graphs are constructed by …

A survey on semantic processing techniques

R Mao, K He, X Zhang, G Chen, J Ni, Z Yang… - Information …, 2024 - Elsevier
Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

UniRE: A unified label space for entity relation extraction

Y Wang, C Sun, Y Wu, H Zhou, L Li, J Yan - arXiv preprint arXiv …, 2021 - arxiv.org
Many joint entity relation extraction models setup two separated label spaces for the two sub-
tasks (ie, entity detection and relation classification). We argue that this setting may hinder …