Same Sentiment Classification Train/Dev/Test Pair IDs

This "dataset" only includes the compiled pairings of the Yelp Business Review Dataset. To get access to the actual review texts, please follow the instructions on the Yelp Dataset webpage. The data format is <em>JSONlines</em>.<br> Python Load Example: <pre><code class="language-python">import pandas as pd traindev_df = pd.read_json("df_traindev.jsonl", lines=True) test_df = pd.read_json("df_test.jsonl", lines=True) # example access to single business/review id s1_bid = test_df.iloc[0]["sent1_business_id"] s1_rid = test_df.iloc[0]["sent1_review_id"] s2_bid = test_df.iloc[0]["sent2_business_id"] s2_rid = test_df.iloc[0]["sent2_review_id"] label = test_df.iloc[0]["is_same_side"]</code></pre> See documentation at: Yelp Dataset Schemata (only <em>business.json</em> and <em>review.json</em> were used) Yelp Business Category Hierarchy (download the json file as <em>all_category_list.json</em>) For details on how the data was compiled and used in our experiments, please refer to our code repository. Other derived data splits can be reproduced deterministically by using the same random seed as in our experiments.本数据集仅包含经整理配对的Yelp商业评论数据集（Yelp Business Review Dataset）样本对。若需获取原始评论文本，请参照Yelp数据集官方网页中的操作指引。数据格式为JSON行格式（JSONlines）。Python加载示例：<pre><code class="language-python">import pandas as pd traindev_df = pd.read_json("df_traindev.jsonl", lines=True) test_df = pd.read_json("df_test.jsonl", lines=True) # example access to single business/review id s1_bid = test_df.iloc[0]["sent1_business_id"] s1_rid = test_df.iloc[0]["sent1_review_id"] s2_bid = test_df.iloc[0]["sent2_business_id"] s2_rid = test_df.iloc[0]["sent2_review_id"] label = test_df.iloc[0]["is_same_side"]</code></pre>相关文档请参阅：Yelp数据集架构（仅使用了business.json与review.json文件）、Yelp商业分类层级体系（可将对应JSON文件下载为all_category_list.json）。有关数据集的整理流程及实验应用细节，请参阅我们的代码仓库。若需复现其他衍生数据划分方案，可使用与本实验相同的随机种子进行确定性复现。