Beginner score
55/100
Competition workspace
适合已有中文 NLP 和任务型对话处理经验、想做槽值共指消解的参赛者。你需要能处理按词切分的多轮对话，并理解说话者、命名实体和成分句法等结构化输入及全局 span 索引。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
55/100
Learning value
58/100
Estimated effort
10-30 hours
Metric
Official scoring is published on the Ba…
适合已有中文 NLP 和任务型对话处理经验、想做槽值共指消解的参赛者。你需要能处理按词切分的多轮对话，并理解说话者、命名实体和成分句法等结构化输入及全局 span 索引。
Taken from the competition's official page.
RiSAWOZ Chinese multi-domain task-oriented dialogue dataset in JSONLines format.
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
中文自然语言处理
共指消解建模
任务型对话数据处理
JSON Lines 读写
span 索引标注
PyTorch 或飞桨
The real friction is usually not library usage. It is validation, time allocation, and task framing.
核心难点是跨多轮对话追踪同一槽值的不同指称，并在多个候选实体间正确建立 cluster；这要求同时处理远距离上下文和多槽值指称。提交也需将预测结果整理为单个 UTF-8 JSON 文件中的 span-index cluster，并附完整代码与系统报告。
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
How to learn feature engineering, validation, and competition workflow without heavy hardware.
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