update_doc

Author: yangheng95

README.MD

@@ -20,7 +20,7 @@
 - [Aspect-based sentiment classification (Multilingual)](https://huggingface.co/spaces/yangheng/PyABSA-APC) 
 - [Aspect term extraction & sentiment classification (Multilingual)](https://huggingface.co/spaces/yangheng/PyABSA-ATEPC)
 - [方面术语提取和情感分类（中文）](https://huggingface.co/spaces/yangheng/PyABSA-ATEPC-Chinese)
-- 
+
 ## Package Overview
 
 <table>
@@ -111,7 +111,7 @@ examples = ['But the staff was so nice to us .',
             ]
 
 inference_source = ABSADatasetList.Restaurant14
-aspect_extractor = ATEPCCheckpointManager.get_aspect_extractor(checkpoint='english')
+aspect_extractor = ATEPCCheckpointManager.get_aspect_extractor(checkpoint='multilingual2')
 atepc_result = aspect_extractor.extract_aspect(inference_source=inference_source,
                                                save_result=True,
                                                print_result=True,  # print the result
@@ -128,6 +128,7 @@ available checkpoints, you can use the following code and load the checkpoint by
 ```python3
 from pyabsa import available_checkpoints
 
+# The results of available_checkpoints() depend on the PyABSA version
 checkpoint_map = available_checkpoints()  # show available checkpoints of PyABSA of current version 
 ```
 

readme/dataset_readme.md

@@ -20,23 +20,24 @@
 
 More datasets are available at [ABSADatasets](https://github.com/yangheng95/ABSADatasets).
 
-1. Twitter
-2. Laptop14
-3. Restaurant14
-4. Restaurant15
-5. Restaurant16
-6. Phone
-7. Car
-8. Camera
-9. Notebook
-10. MAMS
-11. TShirt
-12. Television
-13. MOOC
-14. Shampoo (The annotation of this dataset is highly different from other datasets, please dont mix this dataset with other dataset)
-15. Yelp
-
-You don't have to download the datasets, as the datasets will be downloaded automatically.
+- MAMS https://github.com/siat-nlp/MAMS-for-ABSA
+- SemEval 2014: https://alt.qcri.org/semeval2014/task4/index.php?id=data-and-tools
+- SemEval 2015: https://alt.qcri.org/semeval2015/task12/index.php?id=data-and-tools
+- Chinese: https://www.sciencedirect.com/science/article/abs/pii/S0950705118300972?via%3Dihub
+- Shampoo: [brightgems@GitHub](https://github.com/brightgems/ABSADatasets)
+- MOOC: [jmc-123@GitHub](https://github.com/jmc-123/ABSADatasets) with GPL License
+- Twitter: https://dl.acm.org/doi/10.5555/2832415.2832437
+- Television & TShirt: https://github.com/rajdeep345/ABSA-Reproducibility
+- Yelp: [WeiLi9811@GitHub](https://github.com/WeiLi9811)
+- SemEval2016Task5: [YaxinCui@GitHub](https://github.com/YaxinCui/ABSADataset)
+  - Arabic Hotel Reviews
+  - Dutch Restaurant Reviews
+  - English Restaurant Reviews
+  - French Restaurant Reviews
+  - Russian Restaurant Reviews
+  - Spanish Restaurant Reviews
+  - Turkish Restaurant Reviews
+  You don't have to download the datasets, as the datasets will be downloaded automatically.
 
 ## Annotate Your Own Dataset