Robust Entity Linking via Random Walks

By Zhaochen Guo, Denilson Barbosa. 2014

86 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Extraction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Denilson Barbosa
2. Zhaochen Guo
3. Guangyao Chen
4. Guangwu Qian
5. Pengcheng Gao
6. Xiao Wang
7. Xiaoyong Wei
8. Wen Gao

In Information Extraction

1. Denilson Barbosa
2. Zhaochen Guo

Citations in the corpus

• ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning (2021, neutral): “– KILT: FEVER (Thorne et al., 2018), AIDA (Yosef et al., 2011), WNED (Guo & Barbosa, 2014), T-REx (Guo & Barbosa, 2014), NQ (Kwiatkowski et al., 2019), HoPo (Yang et al., 2018), TQA (Joshi et al., 2017), ELI5 (Fan et al., 2019), WoW (Dinan et al., 2019).”
• Robust named entity disambiguation with random walks (2018, methodology): “We refer to previous work [10] for the tuning of the parameters in our approach.”
• Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey (2023, background): “Entity linking, linking entities from a knowledge base to the corresponding textual mentions in a corpus, can also evaluate how well a model understands the factual knowledge [231].”