Update files from the datasets library (from 1.7.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.7.0

README.md

@@ -20,6 +20,7 @@ task_categories:
 task_ids:
 - sentiment-scoring
 - structure-prediction-other-pos-tagging
+paperswithcode_id: null
 ---
 
 # Dataset Card for SentiWS
@@ -27,12 +28,12 @@ task_ids:
 ## Table of Contents
 - [Dataset Description](#dataset-description)
   - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
   - [Languages](#languages)
 - [Dataset Structure](#dataset-structure)
   - [Data Instances](#data-instances)
-  - [Data Fields](#data-instances)
-  - [Data Splits](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
 - [Dataset Creation](#dataset-creation)
   - [Curation Rationale](#curation-rationale)
   - [Source Data](#source-data)

senti_ws.py

@@ -120,13 +120,13 @@ class SentiWS(datasets.GeneratorBasedBuilder):
         # TODO: This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method.
         # It is in charge of opening the given file and yielding (key, example) tuples from the dataset
         # The key is not important, it's more here for legacy reason (legacy from tfds)
-        for filepath in sourcefiles:
+        for file_idx, filepath in enumerate(sourcefiles):
             with open(filepath, encoding="utf-8") as f:
                 for id_, row in enumerate(f):
                     word = row.split("|")[0]
                     if self.config.name == "pos-tagging":
                         tag = row.split("|")[1].split("\t")[0]
-                        yield id_, {"word": word, "pos-tag": tag}
+                        yield f"{file_idx}_{id_}", {"word": word, "pos-tag": tag}
                     else:
                         sentiscore = row.split("|")[1].split("\t")[1]
-                        yield id_, {"word": word, "sentiment-score": float(sentiscore)}
+                        yield f"{file_idx}_{id_}", {"word": word, "sentiment-score": float(sentiscore)}