Create Sample_Generate_dataset_file.py

Sample_Generate_dataset_file.py

@@ -0,0 +1,71 @@
+"""
+create_cloze_qa_dataset.py
+-------------------------------------
+Generate Cloze-style QA dataset from WikiText-2.
+Each sentence produces one 'fill-in-the-blank' question
+with a single correct answer.
+
+Output: JSONL files for train / validation / test.
+"""
+
+from datasets import load_dataset
+import re
+import json
+from pathlib import Path
+import random
+
+# Load WikiText-2
+print("🔹 Loading WikiText-2 dataset ...")
+dataset = load_dataset("wikitext", "wikitext-2-raw-v1")
+
+# Output directories
+output_dir = Path("cloze_qa_dataset")
+output_dir.mkdir(exist_ok=True, parents=True)
+
+def create_cloze_question(sentence: str):
+    """
+    Convert a sentence into a Cloze-style question by masking one entity/keyword.
+    Returns (question, answer) or None if unsuitable.
+    """
+    words = re.findall(r"\b[A-Z][a-zA-Z]+\b", sentence)  # find capitalized words (possible entities)
+    if not words:
+        return None
+
+    answer = random.choice(words)
+    question = sentence.replace(answer, "____", 1)
+    if question == sentence or len(answer) < 3:
+        return None
+
+    return question.strip(), answer.strip()
+
+def generate_qa_split(split_name, data):
+    """
+    Generate QA pairs for each sentence in the given split.
+    """
+    output_path = output_dir / f"{split_name}.jsonl"
+    count = 0
+    with open(output_path, "w", encoding="utf-8") as f:
+        for doc_id, text in enumerate(data["text"]):
+            if not text.strip():
+                continue
+            sentences = re.split(r'(?<=[.!?]) +', text.strip())
+            for sent_id, sent in enumerate(sentences):
+                qa = create_cloze_question(sent)
+                if qa:
+                    question, answer = qa
+                    record = {
+                        "doc_id": doc_id,
+                        "sent_id": sent_id,
+                        "title": None,
+                        "question": question,
+                        "answer": answer
+                    }
+                    f.write(json.dumps(record, ensure_ascii=False) + "\n")
+                    count += 1
+        print(f" Saved {count} QA pairs to {output_path}")
+
+# Generate datasets
+for split in ["train", "validation", "test"]:
+    generate_qa_split(split, dataset[split])
+
+print("\nAll splits processed and saved successfully")