corpus script generation

.gitignore

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+.venv

README.md

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 ---
 license: mit
 ---
+# Corpus ItaIst

corpus.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:76dad0b3ce089f1ad6e72615ea785fc2b7e4f3a9ef1c61876e82d2abddee1723
+size 14025525

corpus.tsv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3f2fceef17df443a863579507600071fe3274b429c9886656a9b2de2104ea691
+size 14024853

document_to_corpus.py

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+import os
+
+import pandas as pd
+
+BASE_DIR = os.path.join(".")
+
+if __name__ == "__main__":
+    chapters = []
+
+    for root, dirs, files in os.walk(os.path.join(BASE_DIR, "documents")):
+        if "extracted_text.md" in files:
+            with open(os.path.join(root, "extracted_text.md"), "r", encoding="utf-8") as file:
+                full_path = os.path.join(root, "extracted_text.md")
+                text = file.read()
+                lines = text.split("\n")
+                chap_indices = [i for i in range(len(lines)) if lines[i].startswith("# ")]
+                for i in range(len(chap_indices)):
+                    next_index = chap_indices[i + 1] if i < len(chap_indices) - 1 else len(lines)
+
+                    title = lines[chap_indices[i]][2:].strip()
+
+                    content = '\n'.join(lines[chap_indices[i] + 1:next_index])
+                    content = '\n'.join(line.rstrip() for line in content.split("\n"))
+                    content = content.rstrip()
+
+                    chapters.append({
+                        'region': full_path.split('\\')[-5],
+                        'topic': full_path.split('\\')[-4],
+                        'document_type': full_path.split('\\')[-3],
+                        'entity': full_path.split('\\')[-2].split('_')[1],
+                        'document_date': full_path.split('\\')[-2].split('_')[0],
+                        'document_id': full_path.split('\\')[-2].split('_')[2],
+                        'progress': i+1,
+                        "title": title,
+                        "content": content
+                    })
+
+    print(chapters[0])
+
+    df = pd.DataFrame(chapters).sort_values(by=['region', 'topic', 'document_type', 'document_id', 'progress'])
+    df.to_csv(os.path.join(BASE_DIR, 'corpus.csv'), index=False)
+    df.to_csv(os.path.join(BASE_DIR, 'corpus.tsv'), sep='\t', index=False)
+    df.to_excel(os.path.join(BASE_DIR, 'corpus.xlsx'), index=False)

requirements.txt

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+pandas==2.2.3
+openpyxl==3.1.5