Sentence Position Prediction Dataset
Data Example
{
"story":
"为了证明自己看见了这一切,路过银树林时,守望星折了一根小树枝。[MASK]丽娜听到树枝折断的声音时,回头问:“什么声音?”[MASK]“什么声音也没有。”[MASK]她的大姐说,“可能是哪座城堡的塔楼里,猫头鹰在叫唤。”[MASK]她讲话的时候,迈克悄悄地溜到前头,上了楼梯,第一个进了公主们的房间。[MASK]他推开窗户,顺着藤条滑了下去。[MASK]到花园的时候,太阳刚刚开始升起,他要开始工作了。[MASK]这一天,迈克捆扎鲜花的时候,故意把那根银色的树枝扎进了献给小公主的花里。[MASK]不过,她没有告诉姐姐们。",
"sentence":
"丽娜发现银树枝时,吃惊极了。",
"label":
8
}
- "Story" (
str
):input story,<MASK>
means the candidate position - "sentence" (
str
):the removed sentence - "label" (
int
): label=$l$ means the $l$-th position is correct.
Evaluation
The prediction result should have the same format with test.jsonl
python eval.py prediction_file test.jsonl
We use accuracy as the evaluation metric. The output of the script eval.py
is a dictionary as follows:
{"accuracy": _}