Create create.py

create.py

@@ -0,0 +1,72 @@
+from datasets import Dataset, load_dataset
+
+ds: Dataset = load_dataset("DDSC/partial-danish-gigaword-no-twitter")  # type: ignore
+ds = ds["train"]
+# filter to only include spontaneous speech
+ds = ds.filter(lambda x: x["source"] == "spont", num_proc=6)
+
+
+
+texts = ds["text"]
+
+
+def remove_taler(text):
+    if text.startswith("Taler"):
+        text = text.split(":")[1:]
+        text = ":".join(text)
+    return text.strip()
+
+
+qa_pairs = []
+for text in texts:
+    lines = text.split("\n")
+    lines = [remove_taler(line) for line in lines]
+    questions = [
+        (i, text)
+        for i, text in enumerate(lines)
+        if len(text.split(" ")) > 7 and text.endswith("?")
+    ]
+
+    qa_pairs_ = [{"question": lines[i], "answer": lines[i + 1]} for i, _ in questions]
+    qa_pairs += qa_pairs_
+
+
+# filter qa pairs
+def get_length_of_pair(qa: dict):
+    return len(qa["question"].split(" ")) + len(qa["answer"].split(" "))
+
+
+def get_min_length_of_pair(qa: dict):
+    return min(len(qa["question"].split(" ")), len(qa["answer"].split(" ")))
+
+
+qa_pairs = [
+    qa
+    for qa in qa_pairs
+    if get_length_of_pair(qa) < 20 and get_min_length_of_pair(qa) > 4
+]
+
+
+# create dataset
+qa_ds = Dataset.from_list(qa_pairs)
+
+# add readme
+qa_ds.info.description = """# Spontanous speech QA
+
+This dataset contains QA pairs from the spontaneous speech subsection of the Danish Gigaword. 
+The dataset is created from the [DDSC dataset](DDSC/partial-danish-gigaword-no-twitter) and 
+filtered to only include QA pairs where the question is less than 20 tokens and the answer is
+at least 4 tokens long.
+
+To find out more about the creation see the accompanying script.
+"""
+
+qa_ds.info.license = ds[0]["LICENSE"]
+qa_ds.info.dataset_name = "Spontanous Speech QA"
+
+
+# split dataset
+qa_ds = qa_ds.train_test_split(test_size=0.2)
+
+# upload dataset
+qa_ds.push_to_hub("spontanous-speech-qa")