14. compile challenging absa datasets and add readme for source credit

[Nana2929]

1. See Difficult SA Dataset Survey
2. 預計納入 Dialogue ABSA, Structured Sentiment Analysis（好像有三個 English 的 datasets，domain 是大學、政治類的）, MAMS, ARTS。語言以中文和英文為主。
3. 預計下載資料，確認資料類型。 （確認 Prompt）

[Nana2929]

Classic

• [ ] SemEval We need triplet data, see Peng https://github.com/xuuuluuu/SemEval-Triplet-data Source Credits (Ack under this repo): "Our datasets originate from SemEval Challenges (Pontiki 2014; 2015; 2016). The annotation (opinion label) is derived from (Fan et al. 2019), where they already annotated opinion terms."

Robustness

• [x] ARTS: https://github.com/zhijing-jin/ARTS_TestSet
• [x] MAMS: separate ATSA and ACSA, https://github.com/siat-nlp/MAMS-for-ABSA/tree/master/data

Dialogue

• [x] DiaASQ (Laptop/3C domain) https://github.com/unikcc/DiaASQ
• [x] CASA (Celeb/影視）https://github.com/freesunshine0316/lab-conv-asa

[Nana2929]

Large Dataset (SA)

• [ ] Yelp Dataset