Adding prompt and supporting text for Source A

aes_enem_dataset.py

@@ -71,6 +71,8 @@ ESSAY_TO_IGNORE = [
 CSV_HEADER = [
     "id",
     "id_prompt",
+    "prompt",
+    "supporting_text",
     "title",
     "essay",
     "grades",
@@ -138,6 +140,8 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
             {
                 "id": datasets.Value("string"),
                 "id_prompt": datasets.Value("string"),
+                "prompt": datasets.Value("string"),
+                "supporting_text": datasets.Value("string"),
                 "essay_title": datasets.Value("string"),
                 "essay_text": datasets.Value("string"),
                 "grades": datasets.Sequence(datasets.Value("int16")),
@@ -341,13 +345,13 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
         if self.config.name == "sourceAWithGraders":
             grader_a, grader_b = self._parse_graders_data(dirname)
             grader_a_data = pd.merge(
-                train_df[["id", "id_prompt","essay"]],
+                train_df[["id", "id_prompt","essay", "prompt", "supporting_text"]],
                 grader_a.drop(columns=['essay']),
                 on=["id", "id_prompt"],
                 how="inner",
             )
             grader_b_data = pd.merge(
-                train_df[["id", "id_prompt","essay"]],
+                train_df[["id", "id_prompt","essay", "prompt", "supporting_text"]],
                 grader_b.drop(columns=['essay']),
                 on=["id", "id_prompt"],
                 how="inner",
@@ -356,13 +360,13 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
             train_df = pd.concat([train_df, grader_b_data])
 
             grader_a_data = pd.merge(
-                val_df[["id", "id_prompt","essay"]],
+                val_df[["id", "id_prompt","essay", "prompt", "supporting_text"]],
                 grader_a.drop(columns=['essay']),
                 on=["id", "id_prompt"],
                 how="inner",
             )
             grader_b_data = pd.merge(
-                val_df[["id", "id_prompt","essay"]],
+                val_df[["id", "id_prompt","essay", "prompt", "supporting_text"]],
                 grader_b.drop(columns=['essay']),
                 on=["id", "id_prompt"],
                 how="inner",
@@ -371,13 +375,13 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
             val_df = pd.concat([val_df, grader_b_data])
 
             grader_a_data = pd.merge(
-                test_df[["id", "id_prompt","essay"]],
+                test_df[["id", "id_prompt","essay", "prompt", "supporting_text"]],
                 grader_a.drop(columns=['essay']),
                 on=["id", "id_prompt"],
                 how="inner",
             )
             grader_b_data = pd.merge(
-                test_df[["id", "id_prompt","essay"]],
+                test_df[["id", "id_prompt","essay", "prompt", "supporting_text"]],
                 grader_b.drop(columns=['essay']),
                 on=["id", "id_prompt"],
                 how="inner",
@@ -413,6 +417,8 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
                 yield i, {
                     "id": row["id"],
                     "id_prompt": row["id_prompt"],
+                    "prompt": row['prompt'],
+                    "supporting_text": row["supporting_text"],
                     "essay_title": row["title"],
                     "essay_text": row["essay"],
                     "grades": grades,
@@ -633,6 +639,37 @@ class HTMLParser:
                     new_list.append(phrase)
             return new_list
 
+    def _clean_string(self, sentence):
+        sentence = sentence.replace("\xa0","").replace("\u200b","")
+        sentence = sentence.replace(".",". ").replace("?","? ").replace("!", "! ").replace(")",") ").replace(":",": ").replace("”", "” ")
+        sentence = sentence.replace("  ", " ").replace(". . . ", "...")
+        sentence = sentence.replace("(editado)", "").replace("(Editado)","")
+        sentence = sentence.replace("(editado e adaptado)", "").replace("(Editado e adaptado)", "")
+        sentence = sentence.replace(". com. br", ".com.br")
+        sentence = sentence.replace("[Veja o texto completo aqui]", "")
+        return sentence 
+
+    def _get_supporting_text(self, soup):
+        if self.sourceA:
+            textos = soup.find_all("ul", class_="article-wording-item")
+            resposta = []
+            for t in textos[:-1]:
+                resposta.append(t.find("h3", class_="item-titulo").get_text().replace("\xa0",""))
+                resposta.append(self._clean_string(t.find("div", class_="item-descricao").get_text()))
+            return resposta
+        else:
+            return ""
+        
+    def _get_prompt(self, soup):
+        if self.sourceA:
+            prompt = soup.find("div", class_="text").find_all("p")
+            if len(prompt[0].get_text()) < 2:
+                return [prompt[1].get_text().replace("\xa0","")]
+            else:
+                return [prompt[0].get_text().replace("\xa0","")]
+        else: 
+            return ""
+
     def parse(self, config_name):
         for key, filepath in self.paths_dict.items():
             if key != config_name:
@@ -670,6 +707,12 @@ class HTMLParser:
                     essay_year = self._get_essay_year(
                         self.apply_soup(prompt, "Prompt.html")
                     )
+                    essay_supporting_text = "\n".join(self._get_supporting_text(
+                        self.apply_soup(prompt, "Prompt.html")
+                    ))
+                    essay_prompt = "\n".join(self._get_prompt(
+                        self.apply_soup(prompt, "Prompt.html")
+                    ))
                     for essay in prompt_essays:
                         soup_text = self.apply_soup(prompt, essay)
                         if essay == "Prompt.html":
@@ -685,6 +728,8 @@ class HTMLParser:
                             [
                                 essay,
                                 prompt_folder,
+                                essay_prompt,
+                                essay_supporting_text,
                                 essay_title,
                                 essay_text,
                                 essay_grades,