Fix inaccuracies in the dataset card

README.md

@@ -293,7 +293,7 @@ dataset_info:
 
 - **Webpage:** https://registry.opendata.aws/amazon-reviews-ml/
 - **Paper:** https://arxiv.org/abs/2010.02573
-- **Point of Contact:** multilingual-reviews-dataset@amazon.com
+- **Point of Contact:** [multilingual-reviews-dataset@amazon.com](mailto:multilingual-reviews-dataset@amazon.com)
 
 ### Dataset Summary
 
@@ -319,14 +319,14 @@ Each data instance corresponds to a review. The original JSON for an instance lo
 
 ```json
 {
-    "review_id":"de_0784695",
-    "product_id":"product_de_0572654",
-    "reviewer_id":"reviewer_de_0645436",
-    "stars":"1",
-    "review_body":"Leider, leider nach einmal waschen ausgeblichen . Es sieht super h\u00fcbsch aus , nur leider stinkt es ganz schrecklich und ein Waschgang in der Maschine ist notwendig ! Nach einem mal waschen sah es aus als w\u00e4re es 10 Jahre alt und hatte 1000 e von Waschg\u00e4ngen hinter sich :( echt schade !",
-    "review_title":"Leider nicht zu empfehlen",
-    "language":"de",
-    "product_category":"home"
+    "review_id": "de_0784695",
+    "product_id": "product_de_0572654",
+    "reviewer_id": "reviewer_de_0645436",
+    "stars": "1",
+    "review_body": "Leider, leider nach einmal waschen ausgeblichen . Es sieht super h\u00fcbsch aus , nur leider stinkt es ganz schrecklich und ein Waschgang in der Maschine ist notwendig ! Nach einem mal waschen sah es aus als w\u00e4re es 10 Jahre alt und hatte 1000 e von Waschg\u00e4ngen hinter sich :( echt schade !",
+    "review_title": "Leider nicht zu empfehlen",
+    "language": "de",
+    "product_category": "home"
 }
 ```
 
@@ -343,7 +343,7 @@ Each data instance corresponds to a review. The original JSON for an instance lo
 
 ### Data Splits
 
-Each language configuration comes with it's own `train`, `validation`, and `test` splits. The `all_languages` split
+Each language configuration comes with its own `train`, `validation`, and `test` splits. The `all_languages` split
 is simply a concatenation of the corresponding split across all languages. That is, the `train` split for
 `all_languages` is a concatenation of the `train` splits for each of the languages and likewise for `validation` and
 `test`.
@@ -383,9 +383,12 @@ N/A
 
 ### Personal and Sensitive Information
 
-Amazon Reviews are submitted by users with the knowledge and attention of being public. The reviewer ID's included in
-this dataset are quasi-anonymized, meaning that they are disassociated from the original user profiles. However,
-these fields would likely be easy to deannoymize given the public and identifying nature of free-form text responses.
+According to the original dataset [license terms](https://docs.opendata.aws/amazon-reviews-ml/license.txt), you may not:
+- link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or 
+- attempt to determine the identity of the author of any content in the Reviews Corpus.
+
+If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically
+terminate without prejudice to any of the other rights or remedies Amazon may have.
 
 ## Considerations for Using the Data
 
@@ -397,15 +400,14 @@ the languages included here is relatively high resource and well studied.
 
 ### Discussion of Biases
 
-The data included here are from unverified consumers. Some percentage of these reviews may be fake or contain
-misleading or offensive language. 
+The dataset contains only reviews from verified purchases (as described in the paper, section 2.1), and the reviews
+should conform the [Amazon Community Guidelines](https://www.amazon.com/gp/help/customer/display.html?nodeId=GLHXEX85MENUE4XF).
+
 ### Other Known Limitations
 
 The dataset is constructed so that the distribution of star ratings is balanced. This feature has some advantages for
 purposes of classification, but some types of language may be over or underrepresented relative to the original
-distribution of reviews to acheive this balance.
-
-[More Information Needed]
+distribution of reviews to achieve this balance.
 
 ## Additional Information
 
@@ -418,6 +420,10 @@ Published by Phillip Keung, Yichao Lu, György Szarvas, and Noah A. Smith. Manag
 Amazon has licensed this dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc.  A copy of the agreement can be found at the dataset webpage here:
 https://docs.opendata.aws/amazon-reviews-ml/license.txt
 
+By accessing the Multilingual Amazon Reviews Corpus ("Reviews Corpus"), you agree that the Reviews Corpus is an Amazon Service subject to the [Amazon.com Conditions of Use](https://www.amazon.com/gp/help/customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088) and you agree to be bound by them, with the following additional conditions:
+
+In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have.
+
 ### Citation Information
 
 Please cite the following paper (arXiv) if you found this dataset useful:
@@ -435,4 +441,4 @@ Phillip Keung, Yichao Lu, György Szarvas and Noah A. Smith. “The Multilingual
 
 ### Contributions
 
-Thanks to [@joeddav](https://github.com/joeddav) for adding this dataset.
+Thanks to [@joeddav](https://github.com/joeddav) for adding this dataset.