Update Naija-Lexicons.py

Naija-Lexicons.py

@@ -54,7 +54,8 @@ import pandas as pd
 
 import datasets
 
-LANGUAGES = ["hausa", "igbo", "yoruba"]
+#LANGUAGES = ["hausa", "igbo", "yoruba"]
+TYPES = ['manual-sentiment', 'translated-sentiment', 'translated-emotion']
 
 class NaijaLexiconsConfig(datasets.BuilderConfig):
     """BuilderConfig for NaijaLexicons"""
@@ -64,9 +65,9 @@ class NaijaLexiconsConfig(datasets.BuilderConfig):
         text_features,
         label_column,
         label_classes,
-        manual_sentiment_url,
-        translated_sentiment_url,
-        translated_emotion_url,
+        hau_url,
+        ibo_url,
+        yor_url,
         citation,
         **kwargs,
     ):
@@ -88,9 +89,9 @@ class NaijaLexiconsConfig(datasets.BuilderConfig):
         self.text_features = text_features
         self.label_column = label_column
         self.label_classes = label_classes
-        self.manual_sentiment_url = manual_sentiment_url
-        self.translated_sentiment_url = translated_sentiment_url
-        self.translated_emotion_url = translated_emotion_url
+        self.hau_url = hau_url
+        self.ibo_url = ibo_url
+        self.yor_url = yor_url
         self.citation = citation
 
 
@@ -99,24 +100,61 @@ class NaijaLexicons(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = []
 
-    for lang in LANGUAGES:
-        BUILDER_CONFIGS.append(
-            NaijaLexiconsConfig(
-                name=lang,
-                description=textwrap.dedent(
-                    f"""{_DESCRIPTION}"""
+    for t in TYPES:
+        if t == 'translated-emotion':
+            BUILDER_CONFIGS.append(
+                NaijaLexiconsConfig(
+                    name=t,
+                    description=textwrap.dedent(
+                        f"""{_DESCRIPTION}"""
+                    ),
+                    text_features={"word": "word", "machine": "machine", "human": "human", "emotion_intensity_score": "emotion_intensity_score"},
+                    label_classes=["surprise", "fear", "anticipation", "anger", "joy", "trust", "disgust", "sadness"],
+                    label_column="label",
+                    hau_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/hausa.csv",
+                    ibo_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/igbo.csv",
+                    yor_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/yoruba.csv",
+                    citation=textwrap.dedent(
+                        f"""{_CITATION}"""
+                    ),
                 ),
-                text_features={"word": "word", "machine": "machine", "human": "human", "emotion_intensity_score": "emotion_intensity_score"},
-                label_classes=["positive", "negative", "surprise", "fear", "anticipation", "anger", "joy", "trust", "disgust", "sadness"],
-                label_column="label",
-                manual_sentiment_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/manual-sentiment/huggingface/{lang}.csv",
-                translated_sentiment_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/translated-sentiment/huggingface/{lang}.csv",
-                translated_emotion_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/translated-emotion/huggingface/{lang}.csv",
-                citation=textwrap.dedent(
-                    f"""{_CITATION}"""
+            )
+        elif t == 'translated-sentiment':
+            BUILDER_CONFIGS.append(
+                NaijaLexiconsConfig(
+                    name=t,
+                    description=textwrap.dedent(
+                        f"""{_DESCRIPTION}"""
+                    ),
+                    text_features={"word": "word", "machine": "machine", "human": "human"},
+                    label_classes=["positive", "negative"],
+                    label_column="label",
+                    hau_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/hausa.csv",
+                    ibo_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/igbo.csv",
+                    yor_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/yoruba.csv",
+                    citation=textwrap.dedent(
+                        f"""{_CITATION}"""
+                    ),
                 ),
-            ),
-        )
+            )
+        else:
+            BUILDER_CONFIGS.append(
+                NaijaLexiconsConfig(
+                    name=t,
+                    description=textwrap.dedent(
+                        f"""{_DESCRIPTION}"""
+                    ),
+                    text_features={"word": "word"},
+                    label_classes=["positive", "negative"],
+                    label_column="label",
+                    hau_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/hausa.csv",
+                    ibo_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/igbo.csv",
+                    yor_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/{t}/huggingface/yoruba.csv",
+                    citation=textwrap.dedent(
+                        f"""{_CITATION}"""
+                    ),
+                ),
+            )
 
     def _info(self):
         features = {text_feature: datasets.Value("string") for text_feature in self.config.text_features}
@@ -130,14 +168,14 @@ class NaijaLexicons(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        manual_sentiment_path = dl_manager.download_and_extract(self.config.manual_sentiment_url)
-        translated_sentiment_path = dl_manager.download_and_extract(self.config.translated_sentiment_url)
-        translated_emotion_path = dl_manager.download_and_extract(self.config.translated_emotion_url)
+        hau_path = dl_manager.download_and_extract(self.config.hau_url)
+        ibo_path = dl_manager.download_and_extract(self.config.ibo_url)
+        yor_path = dl_manager.download_and_extract(self.config.yor_url)
         
         return [
-            datasets.SplitGenerator(name="manual_sentiment", gen_kwargs={"filepath": manual_sentiment_path}),
-            datasets.SplitGenerator(name="translated_sentiment", gen_kwargs={"filepath": translated_sentiment_path}),
-            datasets.SplitGenerator(name="translated_emotion", gen_kwargs={"filepath": translated_emotion_path})
+            datasets.SplitGenerator(name="hausa", gen_kwargs={"filepath": hau_path}),
+            datasets.SplitGenerator(name="igbo", gen_kwargs={"filepath": ibo_path}),
+            datasets.SplitGenerator(name="yoruba", gen_kwargs={"filepath": yor_path})
         ]
 
     def _generate_examples(self, filepath):