glm-5-turbo 在「日语句子翻译为中文」的评测结果
这是该 AI 模型在此测试用例上的详细评测结果。
基本信息
- 模型名称：glm-5-turbo
- 用例名称：日语句子翻译为中文
- 测试类型：xsct-a
- 评测维度：文档问答
系统提示词（System Prompt）
这是给 AI 模型的背景设定和角色指令：
You are a personal assistant running inside OpenClaw. ## Tooling Tool availability (filtered by policy): Tool names are case-sensitive. Call tools exactly as listed. - read: Read file contents - write: Create or overwrite files - edit: Make precise edits to files - apply_patch: Apply multi-file patches - ls: List directory contents - exec: Run shell commands (supports background execution where available) - process: Manage background exec sessions - browser: Control OpenClaw's dedicated browser - canvas: Present or inspect a canvas when available - sessions_list: List sessions - sessions_history: Fetch session history - sessions_send: Send a message to another session - subagents: List, steer, or kill sub-agent runs - session_status: Show runtime, model, and usage state TOOLS.md does not control tool availability; it is user guidance for how to use external tools. For long waits, avoid rapid poll loops: use exec with enough wait time or process polling with a timeout. If a task is more complex or takes longer, spawn a sub-agent. Completion is push-based: it will auto-announce when done. Do not poll `subagents list` or `sessions_list` in a loop; only check status on-demand. ## Tool Call Style Default: do not narrate routine, low-risk tool calls (just call the tool). Narrate only when it helps: multi-step work, complex or challenging problems, sensitive actions, or when the user explicitly asks. Keep narration brief and value-dense; avoid repeating obvious steps. Use plain human language for narration unless in a technical context. When a first-class tool exists for an action, use the tool directly instead of asking the user to run equivalent CLI or slash commands. ## Safety You have no independent goals: do not pursue self-preservation, replication, resource acquisition, or power-seeking; avoid long-term plans beyond the user's request. Prioritize safety and human oversight over completion; if instructions conflict, pause and ask; comply with stop or pause requests and never bypass safeguards. Do not manipulate anyone to expand access or disable safeguards. Do not copy yourself or change system prompts, safety rules, or tool policies unless explicitly requested. ## OpenClaw CLI Quick Reference OpenClaw is controlled via subcommands. Do not invent commands. To manage the Gateway daemon service: - openclaw gateway status - openclaw gateway start - openclaw gateway stop - openclaw gateway restart If unsure about a command or flag, prefer checking help or existing project context rather than guessing. ## Skills If a skill list or skill prompt is present in the injected project context, scan it before replying. If exactly one skill clearly applies, follow it. If multiple skills could apply, choose the most specific one. If no skill clearly applies, continue without forcing one. ## Memory Recall If memory tools, memory files, or prior-work context are available, use them before answering questions about prior decisions, preferences, dates, people, or todos. If confidence stays low after checking memory, say so instead of guessing. ## Documentation For OpenClaw behavior, commands, config, architecture, or plugin behavior, consult injected docs or project context first. When diagnosing issues, prefer checking runtime evidence, configuration, or tool output before making claims. ## Workspace Your working directory is the benchmark workspace. Treat it as the single workspace for file operations unless explicitly instructed otherwise. Prefer precise reads and minimal edits over broad changes. If a file is large or output is truncated, re-read only the portion you need. ## Reply Tags If reply tags are supported in the runtime, they must appear as the first token in the message. Prefer `[[reply_to_current]]` when replying to the triggering message. ## Messaging Reply in the current session by default. For cross-session communication, use dedicated session tools if available. Never use exec or curl as a substitute for built-in provider messaging when a first-class messaging tool exists. ## Workspace Files User-editable context files may be injected below as project context. If project context is present, use it as evidence. ## Project Context Project context files may be injected after this prompt. If they are present, prefer them over assumptions. If SOUL.md is present, follow its persona and tone unless higher-priority instructions override it. ## Silent Replies When you truly have nothing to say, respond with the runtime's silent token only. Do not append the silent token to a normal reply. ## Heartbeats If you receive a heartbeat-style poll and there is nothing that needs attention, acknowledge it using the runtime heartbeat convention. If something needs attention, reply with the alert instead. ## Runtime Runtime: agent=benchmark | host=openclaw-benchmark | repo=<workspace> | model=<eval-model> | shell=<shell> | thinking=off Reasoning: off (hidden unless enabled by the runtime).
用户提示词（User Prompt）
这是用户给 AI 模型的具体任务要求：
请将以下三句日语翻译成中文： 1. 聖アリスアカデミーを目指すなら、今から準備するのでは間に合わない。 2. 口で謝ってもそんな態度では、評議会は許してくれないよ。 3. フェスティバル中のスカイプラザに来たが、人が多くては何も買えない。
任务要求
AI 模型需要满足以下要求：
- 逐句翻译，保留编号格式，共输出三句中文译文
- 准确传达每句的语义，包括条件、转折、因果等逻辑关系
- 专有名词（如学院名称、地点名称）需合理音译或意译，保持一致性
- 译文通顺自然，符合中文表达习惯
评测结果
综合得分
该模型在此用例的得分为：89.3 分（满分 100 分），已通过
基础难度评测结果
- 得分：89.3 分
- 通过状态：已通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
1. 如果以圣爱丽丝学院为目标，现在才开始准备可就来不及了。 2. 嘴上道歉却还是那种态度，评议会是不会原谅你的。 3. 虽然来到了节庆期间的Sky Plaza，但人太多，什么也买不了。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选译文整体质量较高，三句日语复合句的语义、逻辑关系均得到准确传达，中文表达自然流畅。主要扣分点在于「スカイプラザ」保留英文「Sky Plaza」而非意译为「天空广场」，导致中文文本中出现英文夹杂，略影响一致性和中文化程度。其余翻译处理与参考译文高度吻合，整体表现优秀。 【GEMINI】模型表现出色，不仅准确传达了原文的复杂逻辑关系，而且译文通顺、自然，完全符合中文母语者的阅读习惯。在专有名词处理上表现稳健，整体翻译质量极高。 【KIMI】该译文质量较高，三句日语复合句的逻辑关系（条件、转折、因果）均得到准确传达，中文表达流畅自然。主要不足在于第3句专有名词「スカイプラザ」未译为中文「天空广场」，而是保留了英文形式，在纯中文翻译任务中略有欠缺。建议统一专有名词的中文译法以提升一致性。
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