Repository: open-compass/opencompass
Issue: [Bug] 0.5.1版本下，longbench测试summarization任务时均采用rouge_chinese而非rouge，导致分数不正确
Root cause: Configuration Error

### Prerequisite

- [x] I have searched [Issues](https://github.com/open-compass/opencompass/issues/) and [Discussions](https://github.com/open-compass/opencompass/discussions) but cannot get the expected help.
- [x] The bug has not been fixed in the [latest version](https://github.com/open-compass/opencompass).

### Type

I'm evaluating with the officially supported tasks/models/datasets.

### Environment

如题，最近更新opencompass版本到0.5.1后，测试longbench发现总结类任务得分都有下降，排查原因后，发现是打分时调用的Rouge类来自rouge_chinese而非rouge
class LongBenchRougeEvaluator(BaseEvaluator):

    def __init__(self, language: str = 'en') -> None:
        super().__init__()
        assert language in ['en', 'zh']
        self.language = language

    def score(self, predictions: List, references: List) -> dict:
        score = 0.
        for i in range(len(predictions)):
            prediction = predictions[i]
            reference_list = references[i]
            task_score = 0.
            for reference in reference_list:
                if self.language == 'zh':
                    prediction = ' '.join(
                        list(jieba.cut(prediction, cut_all=False)))
                    reference = ' '.join(
                        list(jieba.cut(reference, cut_all=False)))

                rouge = Rouge()
                print(Rouge.__module__) #打印模块名
                try:
                    cur_score = rouge.get_scores([prediction], [reference],
                                                 avg=True)['rouge-l']['f']
                except Exception:
                    cur_score = 0.
                task_score = max(task_score, cur_score)
                print(task_score)

            score += task_score

        score = score / len(predictions) * 100
        return {'score': score}

输出结果：（Rouge来自rouge_chinese），得分比原先下降很多
rouge_chinese.rouge
0.160116443561251
rouge_chinese.rouge
0.1335676585234171

### Reproduces the problem - code/configuration sample

opencompass/datasets/longbench/evaluator.py
class LongBenchRougeEvaluator(BaseEvaluator):

    def __init__(self, language: str = 'en') -> None:
        super().__init__()
        assert language in ['en', 'zh']
        self.language = language

    def score(self, predictions: List, references: List) -> dict:
        score = 0.
        for i in range(len(predictions)):
            prediction = predictions[i]
            reference_list = references[i]
            task_score = 0.
            for reference in reference_list:
                if self.language == 'zh':
                    prediction = ' '.join(
                        list(jieba.cut(prediction, cut_all=False)))
                    reference = ' '.join(
                        list(jieba.cut(reference, cut_all=False)))

                rouge = Rouge()
                print(Rouge.__module__) #打印模块名
                try:
                    cur_score = rouge.get_scores([prediction], [reference],
                                                 avg=True)['rouge-l']['f']
                except Exception:
                    cur_score = 0.
                task_score = max(task_score, cur_score)
                print(task_score)

            score += task_score

        score = score / len(predictions) * 100
        return {'score': score}

### Reproduces the problem - command or script

opencompass --models llama_ASVD_3_8B --datasets longbench_multi_news_gen --debug --reuse 20251216_155939

### Reproduces the problem - error message

none

### Other information

_No response_