new article url

README.md

@@ -104,7 +104,7 @@ Hansel is a high-quality human-annotated Chinese entity linking (EL) dataset, fo
 - The test set contains Few-shot (FS) and zero-shot (ZS) slices, has 10K examples and uses Wikidata as the corresponding knowledge base.
 - The training and validation sets are from Wikipedia hyperlinks, useful for large-scale pretraining of Chinese EL systems.
   
-Please see our [WSDM 2023](https://www.wsdm-conference.org/2023/) paper [**"Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark"**](https://arxiv.org/abs/2207.13005) to learn more about our dataset.
+Please see our [WSDM 2023](https://www.wsdm-conference.org/2023/) paper [**"Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark"**](https://dl.acm.org/doi/10.1145/3539597.3570418) to learn more about our dataset.
 
 For models in the paper and our processed knowledge base, please see our [Github repository](https://github.com/HITsz-TMG/Hansel).
 
@@ -137,11 +137,13 @@ For models in the paper and our processed knowledge base, please see our [Github
 If you find our dataset useful, please cite us.
 
 ```bibtex
-@misc{xu2022hansel,
-  title = {Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark},
+@inproceedings{xu2022hansel,
   author = {Xu, Zhenran and Shan, Zifei and Li, Yuxin and Hu, Baotian and Qin, Bing},
-  publisher = {arXiv},
-  year = {2022},
-  url = {https://arxiv.org/abs/2207.13005}
+  title = {Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark},
+  year = {2023},
+  publisher = {Association for Computing Machinery},
+  url = {https://doi.org/10.1145/3539597.3570418},
+  booktitle = {Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining},
+  pages = {832–840}
 }
 ```