From c83d771923845bf8e8696dd216c70553d0f19f14 Mon Sep 17 00:00:00 2001
From: iomgaa <iomgaaycz@gmail.com>
Date: Sat, 11 Jul 2026 23:14:43 -0400
Subject: [PATCH] feat(question_gen): add deterministic postprocess layer

Add app/question_gen/postprocess.py with zero-LLM deterministic
post-processing for generated questions:

- shuffle_options: deterministic option permutation with answer remapping
- check_referent_blacklist: detect self-referential language (this clip, etc.)
- check_verbatim: word-level n-gram overlap ratio measurement
- has_time_anchor: timestamp and temporal phrase detection
- check_forbidden_material: T1/T7 source material validation
- run_postprocess: orchestration returning PostprocessResult

Tests: 31 unit tests covering all functions.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---
 app/question_gen/postprocess.py | 362 ++++++++++++++++++++++++++++++++
 tests/unit/test_postprocess.py  | 336 +++++++++++++++++++++++++++++
 2 files changed, 698 insertions(+)
 create mode 100644 app/question_gen/postprocess.py
 create mode 100644 tests/unit/test_postprocess.py

diff --git a/app/question_gen/postprocess.py b/app/question_gen/postprocess.py
new file mode 100644
index 0000000..571d3b8
--- /dev/null
+++ b/app/question_gen/postprocess.py
@@ -0,0 +1,362 @@
+"""确定性后处理层 — 零 LLM 的选项洗牌、指代黑名单、逐字重复率、时间锚点、素材禁区检测。
+
+所有函数均为纯函数（给定输入必定产出相同输出），
+用于 pipeline 出题后、门控前的确定性质量检查。
+"""
+
+from __future__ import annotations
+
+import re
+from dataclasses import dataclass
+from typing import TYPE_CHECKING
+
+from loguru import logger
+
+if TYPE_CHECKING:
+    import random
+
+
+# ---------------------------------------------------------------------------
+# 数据结构
+# ---------------------------------------------------------------------------
+
+
+@dataclass(frozen=True)
+class PostprocessResult:
+    """后处理结果汇总。
+
+    属性:
+        options: 洗牌后的选项元组。
+        answer: 重映射后的答案字母。
+        referent_violations: 指代黑名单违规描述列表。
+        verbatim_ratio: 正确选项与来源素材的逐字重复率 [0.0, 1.0]。
+        has_time_anchor: 题目是否包含时间锚点。
+    """
+
+    options: tuple[str, ...]
+    answer: str
+    referent_violations: list[str]
+    verbatim_ratio: float
+    has_time_anchor: bool
+
+
+# ---------------------------------------------------------------------------
+# 指代黑名单（预编译正则）
+# ---------------------------------------------------------------------------
+
+_BLACKLIST_PATTERNS: list[tuple[re.Pattern[str], str]] = [
+    (re.compile(r"this\s+clip", re.IGNORECASE), "this clip"),
+    (re.compile(r"the\s+video", re.IGNORECASE), "the video"),
+    (re.compile(r"this\s+video", re.IGNORECASE), "this video"),
+    (re.compile(r"this\s+scene", re.IGNORECASE), "this scene"),
+    (re.compile(r"the\s+clip", re.IGNORECASE), "the clip"),
+    (re.compile(r"this\s+footage", re.IGNORECASE), "this footage"),
+    (re.compile(r"the\s+footage", re.IGNORECASE), "the footage"),
+    (re.compile(r"上面的片段", re.IGNORECASE), "上面的片段"),
+    (re.compile(r"这段视频", re.IGNORECASE), "这段视频"),
+    (re.compile(r"该视频", re.IGNORECASE), "该视频"),
+    (re.compile(r"这个片段", re.IGNORECASE), "这个片段"),
+    (re.compile(r"视频中", re.IGNORECASE), "视频中"),
+]
+
+
+# ---------------------------------------------------------------------------
+# 时间锚点正则与短语
+# ---------------------------------------------------------------------------
+
+_TIMESTAMP_PATTERN = re.compile(r"\d{1,2}:\d{2}")
+
+_TIME_ANCHOR_PHRASES: list[re.Pattern[str]] = [
+    re.compile(r"at\s+the\s+beginning", re.IGNORECASE),
+    re.compile(r"at\s+the\s+end", re.IGNORECASE),
+    re.compile(r"in\s+the\s+beginning", re.IGNORECASE),
+    re.compile(r"at\s+the\s+start", re.IGNORECASE),
+    re.compile(r"开头", re.IGNORECASE),
+    re.compile(r"结尾", re.IGNORECASE),
+    re.compile(r"末尾", re.IGNORECASE),
+    re.compile(r"片头", re.IGNORECASE),
+    re.compile(r"片尾", re.IGNORECASE),
+]
+
+
+# ---------------------------------------------------------------------------
+# T1 / T7 素材禁区正则
+# ---------------------------------------------------------------------------
+
+# T1: 瞬时动作
+_T1_INSTANT_ACTION_PATTERNS: list[re.Pattern[str]] = [
+    re.compile(r"瞬间|一闪而过|转瞬即逝|一瞬间|刹那", re.IGNORECASE),
+    re.compile(r"flash|instant|split\s*second|blink", re.IGNORECASE),
+]
+
+# T1: 记分牌时序
+_T1_SCOREBOARD_PATTERNS: list[re.Pattern[str]] = [
+    re.compile(r"记分牌|比分.*变|比分.*更新|得分.*变化", re.IGNORECASE),
+    re.compile(r"scoreboard|score\s*(changed|updated|went)", re.IGNORECASE),
+]
+
+# T1: 无对白因果
+_T1_NO_DIALOGUE_CAUSAL_PATTERNS: list[re.Pattern[str]] = [
+    re.compile(r"无对白.*因果|因果.*无法.*判断", re.IGNORECASE),
+    re.compile(r"no\s+dialogue.*caus|cannot.*determin.*caus", re.IGNORECASE),
+]
+
+# T7: 选项重复
+_T7_OPTION_REPETITION_PATTERNS: list[re.Pattern[str]] = [
+    re.compile(r"重复选项|选项.*相同|选项.*重复|完全相同", re.IGNORECASE),
+    re.compile(r"duplicate\s+option|identical\s+option|same\s+option", re.IGNORECASE),
+]
+
+# T7: 计数边界口径含糊
+_T7_COUNTING_AMBIGUITY_PATTERNS: list[re.Pattern[str]] = [
+    re.compile(r"大约.*数量|数量不确定|难以.*计数|不确定.*几|约.*个", re.IGNORECASE),
+    re.compile(r"approximate.*count|uncertain.*number|hard\s+to\s+count", re.IGNORECASE),
+]
+
+
+# ---------------------------------------------------------------------------
+# 公开函数
+# ---------------------------------------------------------------------------
+
+
+def shuffle_options(
+    options: tuple[str, ...],
+    answer: str,
+    rng: random.Random,
+) -> tuple[tuple[str, ...], str]:
+    """确定性洗牌选项并重映射答案字母。
+
+    通过 index permutation 打乱选项顺序，为每个选项重新分配 A/B/C/D 前缀，
+    并将答案字母映射到正确选项的新位置。
+
+    参数:
+        options: 原始选项元组，格式为 ("A. text1", "B. text2", ...)。
+        answer: 原始答案字母（"A"/"B"/"C"/"D"）。
+        rng: 可控随机数生成器（保证确定性）。
+
+    返回:
+        (新选项元组, 新答案字母) — 选项文本不变，仅前缀和顺序改变。
+    """
+    # Phase 1: 提取纯文本（去掉 "X. " 前缀）
+    texts = [opt[3:] for opt in options]
+
+    # Phase 2: 确定原正确选项的文本
+    correct_idx = ord(answer) - ord("A")
+    correct_text = texts[correct_idx]
+
+    # Phase 3: 生成随机排列
+    indices = list(range(len(texts)))
+    rng.shuffle(indices)
+
+    # Phase 4: 按排列重组，分配新前缀
+    new_options: list[str] = []
+    new_answer = ""
+    for new_pos, old_idx in enumerate(indices):
+        letter = chr(ord("A") + new_pos)
+        new_options.append(f"{letter}. {texts[old_idx]}")
+        if texts[old_idx] == correct_text:
+            new_answer = letter
+
+    return tuple(new_options), new_answer
+
+
+def check_referent_blacklist(question_text: str) -> list[str]:
+    """检测题目文本中的自指代语言。
+
+    在 benchmark 题目中，自指代（如 "this clip"、"这段视频"）会泄露视频上下文，
+    使题目脱离视频后无法独立理解。
+
+    参数:
+        question_text: 题目文本。
+
+    返回:
+        违规描述列表，空列表表示通过。
+    """
+    violations: list[str] = []
+    for pattern, label in _BLACKLIST_PATTERNS:
+        if pattern.search(question_text):
+            violations.append(f"检测到自指代: '{label}'")
+    return violations
+
+
+def check_verbatim(
+    question_text: str,
+    correct_option: str,
+    source_texts: list[str],
+    window: int = 6,
+) -> float:
+    """计算正确选项与来源素材的逐字重复率。
+
+    使用滑动窗口 n-gram 集合交集方法：从选项文本提取所有 n-gram，
+    与来源文本的 n-gram 集合求交集，计算重叠比例。
+
+    参数:
+        question_text: 题目文本（当前未使用，预留接口）。
+        correct_option: 正确选项文本（含 "X. " 前缀）。
+        source_texts: 来源素材文本列表。
+        window: n-gram 窗口大小。
+
+    返回:
+        重复率 [0.0, 1.0]。0.0 表示无重叠，1.0 表示完全复制。
+    """
+    # Phase 1: 提取选项纯文本（去掉可能的 "X. " 前缀）
+    option_text = correct_option
+    if len(option_text) >= 3 and option_text[1] == "." and option_text[2] == " ":
+        option_text = option_text[3:]
+
+    # Phase 2: 分词（简单空格分词，转小写）
+    option_words = option_text.lower().split()
+
+    # Phase 3: 选项词数不足窗口大小则无法构成 n-gram
+    if len(option_words) < window:
+        return 0.0
+
+    # Phase 4: 构造选项的 n-gram 集合
+    option_ngrams: set[tuple[str, ...]] = set()
+    for i in range(len(option_words) - window + 1):
+        option_ngrams.add(tuple(option_words[i : i + window]))
+
+    if not option_ngrams:
+        return 0.0
+
+    # Phase 5: 构造来源文本的 n-gram 集合
+    source_ngrams: set[tuple[str, ...]] = set()
+    for source in source_texts:
+        words = source.lower().split()
+        for i in range(len(words) - window + 1):
+            source_ngrams.add(tuple(words[i : i + window]))
+
+    if not source_ngrams:
+        return 0.0
+
+    # Phase 6: 计算交集比例
+    overlap = option_ngrams & source_ngrams
+    return len(overlap) / len(option_ngrams)
+
+
+def has_time_anchor(question_text: str) -> bool:
+    """检测题目中是否包含时间锚点。
+
+    时间锚点包括：数字时间戳（如 "01:30"）和时间短语（如 "at the beginning"、"开头"）。
+
+    参数:
+        question_text: 题目文本。
+
+    返回:
+        True 表示包含时间锚点。
+    """
+    # Phase 1: 检查数字时间戳
+    if _TIMESTAMP_PATTERN.search(question_text):
+        return True
+
+    # Phase 2: 检查时间短语
+    return any(pattern.search(question_text) for pattern in _TIME_ANCHOR_PHRASES)
+
+
+def check_forbidden_material(source_nodes_text: str, task_type: str) -> list[str]:
+    """出题禁区：检测 T1 类素材和 T7 噪声模式。
+
+    T1 类素材（不适合出题的内容）:
+    - 瞬时动作：画面一闪而过，无法稳定观察
+    - 记分牌时序：依赖数字变化的时序信息
+    - 无对白因果：缺乏语言线索的因果推理
+
+    T7 噪声模式（选项质量问题）:
+    - 选项重复：多个选项表述相同
+    - 计数边界口径含糊：数量描述不确定
+
+    参数:
+        source_nodes_text: 来源节点的拼接文本。
+        task_type: 题型名称（用于上下文感知检测）。
+
+    返回:
+        违规描述列表，空列表表示通过。
+    """
+    violations: list[str] = []
+
+    # Phase 1: T1 瞬时动作检测
+    for pattern in _T1_INSTANT_ACTION_PATTERNS:
+        if pattern.search(source_nodes_text):
+            violations.append("T1 违规: 素材包含瞬时动作描述，不适合出题")
+            break
+
+    # Phase 2: T1 记分牌时序检测
+    for pattern in _T1_SCOREBOARD_PATTERNS:
+        if pattern.search(source_nodes_text):
+            violations.append("T1 违规: 素材包含记分牌时序信息，不适合出题")
+            break
+
+    # Phase 3: T1 无对白因果检测
+    for pattern in _T1_NO_DIALOGUE_CAUSAL_PATTERNS:
+        if pattern.search(source_nodes_text):
+            violations.append("T1 违规: 素材缺乏对白因果线索，不适合出题")
+            break
+
+    # Phase 4: T7 选项重复检测
+    for pattern in _T7_OPTION_REPETITION_PATTERNS:
+        if pattern.search(source_nodes_text):
+            violations.append("T7 违规: 素材暗示可能产生重复选项")
+            break
+
+    # Phase 5: T7 计数边界口径含糊检测
+    for pattern in _T7_COUNTING_AMBIGUITY_PATTERNS:
+        if pattern.search(source_nodes_text):
+            violations.append("T7 违规: 素材包含计数边界含糊描述")
+            break
+
+    return violations
+
+
+def run_postprocess(
+    question_text: str,
+    options: tuple[str, ...],
+    answer: str,
+    source_texts: list[str],
+    rng: random.Random,
+) -> PostprocessResult:
+    """编排全部后处理检查，返回汇总结果。
+
+    执行流程:
+    1. 选项洗牌（确定性）
+    2. 指代黑名单检测
+    3. 逐字重复率计算（基于洗牌后的正确选项）
+    4. 时间锚点检测
+
+    参数:
+        question_text: 题目文本。
+        options: 原始选项元组（"A. text", "B. text", ...）。
+        answer: 原始答案字母。
+        source_texts: 来源素材文本列表。
+        rng: 可控随机数生成器。
+
+    返回:
+        PostprocessResult 汇总实例。
+    """
+    # Phase 1: 选项洗牌
+    shuffled_options, new_answer = shuffle_options(options, answer, rng)
+
+    # Phase 2: 指代黑名单
+    referent_violations = check_referent_blacklist(question_text)
+
+    # Phase 3: 逐字重复率（用洗牌后正确选项的文本）
+    correct_idx = ord(new_answer) - ord("A")
+    correct_option_text = shuffled_options[correct_idx]
+    verbatim_ratio = check_verbatim(question_text, correct_option_text, source_texts)
+
+    # Phase 4: 时间锚点
+    time_anchor = has_time_anchor(question_text)
+
+    logger.debug(
+        "后处理完成: referent_violations={}, verbatim_ratio={:.3f}, has_time_anchor={}",
+        len(referent_violations),
+        verbatim_ratio,
+        time_anchor,
+    )
+
+    return PostprocessResult(
+        options=shuffled_options,
+        answer=new_answer,
+        referent_violations=referent_violations,
+        verbatim_ratio=verbatim_ratio,
+        has_time_anchor=time_anchor,
+    )
diff --git a/tests/unit/test_postprocess.py b/tests/unit/test_postprocess.py
new file mode 100644
index 0000000..60ac59d
--- /dev/null
+++ b/tests/unit/test_postprocess.py
@@ -0,0 +1,336 @@
+"""postprocess 模块单元测试 — 选项洗牌、指代黑名单、逐字重复率、时间锚点、素材禁区、run_postprocess 编排。"""
+
+from __future__ import annotations
+
+import random
+
+from app.question_gen.postprocess import (
+    PostprocessResult,
+    check_forbidden_material,
+    check_referent_blacklist,
+    check_verbatim,
+    has_time_anchor,
+    run_postprocess,
+    shuffle_options,
+)
+
+# ---------------------------------------------------------------------------
+# TestShuffleOptions
+# ---------------------------------------------------------------------------
+
+
+class TestShuffleOptions:
+    """选项洗牌确定性与答案重映射测试。"""
+
+    def test_deterministic_with_seed(self) -> None:
+        """相同种子产生相同置换结果。"""
+        options = ("A. 苹果", "B. 香蕉", "C. 橙子", "D. 葡萄")
+        answer = "B"
+        rng1 = random.Random(42)
+        rng2 = random.Random(42)
+
+        result1 = shuffle_options(options, answer, rng1)
+        result2 = shuffle_options(options, answer, rng2)
+
+        assert result1 == result2
+
+    def test_answer_remapped_correctly(self) -> None:
+        """洗牌后 answer 字母始终指向原正确文本。"""
+        options = ("A. 苹果", "B. 香蕉", "C. 橙子", "D. 葡萄")
+        answer = "B"  # 正确文本是 "香蕉"
+
+        # 用多个不同种子确保覆盖不同排列
+        for seed in range(100):
+            rng = random.Random(seed)
+            new_options, new_answer = shuffle_options(options, answer, rng)
+
+            # 答案字母对应的选项文本必须包含 "香蕉"
+            answer_idx = ord(new_answer) - ord("A")
+            assert "香蕉" in new_options[answer_idx], (
+                f"seed={seed}: 新答案 {new_answer} 对应 '{new_options[answer_idx]}'，不含 '香蕉'"
+            )
+
+    def test_all_options_preserved(self) -> None:
+        """洗牌后选项内容集合不变（仅字母前缀重映射）。"""
+        options = ("A. 苹果", "B. 香蕉", "C. 橙子", "D. 葡萄")
+        answer = "A"
+        rng = random.Random(7)
+
+        new_options, _ = shuffle_options(options, answer, rng)
+
+        # 提取纯文本（去除 "X. " 前缀）
+        original_texts = {opt[3:] for opt in options}
+        shuffled_texts = {opt[3:] for opt in new_options}
+        assert original_texts == shuffled_texts
+
+    def test_output_letters_sequential(self) -> None:
+        """洗牌后选项前缀始终为 A/B/C/D 顺序。"""
+        options = ("A. one", "B. two", "C. three", "D. four")
+        answer = "C"
+        rng = random.Random(99)
+
+        new_options, _ = shuffle_options(options, answer, rng)
+        for i, opt in enumerate(new_options):
+            expected_prefix = f"{chr(ord('A') + i)}. "
+            assert opt.startswith(expected_prefix), (
+                f"选项 {i} 应以 '{expected_prefix}' 开头，实际为 '{opt[:3]}'"
+            )
+
+
+# ---------------------------------------------------------------------------
+# TestReferentBlacklist
+# ---------------------------------------------------------------------------
+
+
+class TestReferentBlacklist:
+    """指代黑名单检测测试。"""
+
+    def test_clean_passes(self) -> None:
+        """无自指代语言的正常题目返回空列表。"""
+        q = "What is the main character doing in the kitchen?"
+        violations = check_referent_blacklist(q)
+        assert violations == []
+
+    def test_this_clip_caught(self) -> None:
+        """'this clip' 被检测为违规。"""
+        q = "What happens in this clip after the man enters?"
+        violations = check_referent_blacklist(q)
+        assert len(violations) >= 1
+        assert any("this clip" in v.lower() for v in violations)
+
+    def test_the_video_caught(self) -> None:
+        """'the video' 被检测为违规。"""
+        q = "In the video, what color is the car?"
+        violations = check_referent_blacklist(q)
+        assert len(violations) >= 1
+
+    def test_chinese_referent_caught(self) -> None:
+        """中文自指代 '这段视频' 被检测。"""
+        q = "这段视频中男人在做什么？"
+        violations = check_referent_blacklist(q)
+        assert len(violations) >= 1
+
+    def test_this_scene_caught(self) -> None:
+        """'this scene' 被检测为违规。"""
+        q = "What is shown in this scene before the explosion?"
+        violations = check_referent_blacklist(q)
+        assert len(violations) >= 1
+
+    def test_case_insensitive(self) -> None:
+        """大小写不影响检测。"""
+        q = "What does THIS CLIP show at the end?"
+        violations = check_referent_blacklist(q)
+        assert len(violations) >= 1
+
+
+# ---------------------------------------------------------------------------
+# TestVerbatim
+# ---------------------------------------------------------------------------
+
+
+class TestVerbatim:
+    """逐字重复率检测测试。"""
+
+    def test_zero_overlap(self) -> None:
+        """正确选项与来源文本完全无重叠时返回 0.0。"""
+        ratio = check_verbatim(
+            question_text="What color is the sky?",
+            correct_option="A. The sky is painted in bright orange",
+            source_texts=["A man walks into a store and buys groceries for dinner."],
+            window=6,
+        )
+        assert ratio == 0.0
+
+    def test_full_copy_returns_one(self) -> None:
+        """正确选项完全来自来源文本时返回 1.0。"""
+        source = "The cat sat on the mat near the window looking outside"
+        option = "A. The cat sat on the mat near the window looking outside"
+        ratio = check_verbatim(
+            question_text="What did the animal do?",
+            correct_option=option,
+            source_texts=[source],
+            window=6,
+        )
+        assert ratio == 1.0
+
+    def test_partial(self) -> None:
+        """部分重叠返回 0-1 之间的值。"""
+        source = "The large brown dog jumped over the lazy red fox quickly"
+        # 选项中 6 词窗口 "large brown dog jumped over the" 出现在 source 中
+        option = "A. A large brown dog jumped over the small fence"
+        ratio = check_verbatim(
+            question_text="What happened?",
+            correct_option=option,
+            source_texts=[source],
+            window=6,
+        )
+        assert 0.0 < ratio < 1.0
+
+    def test_empty_source_returns_zero(self) -> None:
+        """来源文本为空列表时返回 0.0。"""
+        ratio = check_verbatim(
+            question_text="What is this?",
+            correct_option="A. Something interesting",
+            source_texts=[],
+            window=6,
+        )
+        assert ratio == 0.0
+
+    def test_short_option_below_window(self) -> None:
+        """选项词数不足窗口大小时仍正常工作（返回 0.0）。"""
+        ratio = check_verbatim(
+            question_text="What?",
+            correct_option="A. Hello world",
+            source_texts=["Some very long source text that goes on and on"],
+            window=6,
+        )
+        assert ratio == 0.0
+
+
+# ---------------------------------------------------------------------------
+# TestTimeAnchor
+# ---------------------------------------------------------------------------
+
+
+class TestTimeAnchor:
+    """时间锚点检测测试。"""
+
+    def test_timestamp(self) -> None:
+        """包含 '01:30' 格式时间戳 → True。"""
+        assert has_time_anchor("What happens at 01:30 in the recording?") is True
+
+    def test_no_anchor(self) -> None:
+        """无任何时间锚点 → False。"""
+        assert has_time_anchor("What is the man doing in the park?") is False
+
+    def test_beginning_phrase(self) -> None:
+        """'at the beginning' → True。"""
+        assert has_time_anchor("At the beginning, what does the woman say?") is True
+
+    def test_chinese_beginning(self) -> None:
+        """'开头' → True。"""
+        assert has_time_anchor("视频开头出现了什么？") is True
+
+    def test_chinese_ending(self) -> None:
+        """'结尾' → True。"""
+        assert has_time_anchor("在视频结尾发生了什么？") is True
+
+    def test_minute_second_format(self) -> None:
+        """'12:45' 格式 → True。"""
+        assert has_time_anchor("At 12:45, who appears on screen?") is True
+
+
+# ---------------------------------------------------------------------------
+# TestCheckForbiddenMaterial
+# ---------------------------------------------------------------------------
+
+
+class TestCheckForbiddenMaterial:
+    """素材禁区检测测试。"""
+
+    def test_clean_material_passes(self) -> None:
+        """正常素材无违规。"""
+        source = "一个男人走进厨房，开始准备晚餐，切菜并烧水。"
+        violations = check_forbidden_material(source, "Action Recognition")
+        assert violations == []
+
+    def test_t1_instant_action_detected(self) -> None:
+        """T1 瞬时动作模式被检测。"""
+        source = "球员瞬间射门得分。一闪而过的画面。"
+        violations = check_forbidden_material(source, "Action Recognition")
+        assert len(violations) >= 1
+
+    def test_t1_scoreboard_temporal_detected(self) -> None:
+        """T1 记分牌时序模式被检测。"""
+        source = "比分从2:1变为3:1，记分牌显示更新。"
+        violations = check_forbidden_material(source, "Counting Problem")
+        assert len(violations) >= 1
+
+    def test_t7_option_repetition_detected(self) -> None:
+        """T7 选项重复模式被检测。"""
+        source = "选项A和选项B完全相同。重复选项无法区分。"
+        violations = check_forbidden_material(source, "Object Recognition")
+        assert len(violations) >= 1
+
+    def test_t7_counting_ambiguity_detected(self) -> None:
+        """T7 计数边界口径含糊被检测。"""
+        source = "大约有三到五个人，数量不确定，难以精确计数。"
+        violations = check_forbidden_material(source, "Counting Problem")
+        assert len(violations) >= 1
+
+
+# ---------------------------------------------------------------------------
+# TestRunPostprocess
+# ---------------------------------------------------------------------------
+
+
+class TestRunPostprocess:
+    """run_postprocess 编排测试。"""
+
+    def test_returns_postprocess_result(self) -> None:
+        """返回类型正确。"""
+        result = run_postprocess(
+            question_text="What is the main character doing?",
+            options=("A. Running", "B. Swimming", "C. Reading", "D. Sleeping"),
+            answer="A",
+            source_texts=["The protagonist goes for a morning jog in the park."],
+            rng=random.Random(42),
+        )
+        assert isinstance(result, PostprocessResult)
+
+    def test_shuffle_applied(self) -> None:
+        """选项顺序被打乱（至少在多次运行中出现过不同排列）。"""
+        options = ("A. Alpha", "B. Beta", "C. Gamma", "D. Delta")
+        answer = "A"
+
+        seen_orders: set[tuple[str, ...]] = set()
+        for seed in range(50):
+            result = run_postprocess(
+                question_text="Pick one",
+                options=options,
+                answer=answer,
+                source_texts=["Unrelated source text about something else entirely."],
+                rng=random.Random(seed),
+            )
+            seen_orders.add(result.options)
+
+        # 50 个不同种子应产生多于 1 种排列
+        assert len(seen_orders) > 1
+
+    def test_referent_violations_populated(self) -> None:
+        """有指代违规时正确填入结果。"""
+        result = run_postprocess(
+            question_text="What happens in this clip?",
+            options=("A. One", "B. Two", "C. Three", "D. Four"),
+            answer="B",
+            source_texts=["Some text here."],
+            rng=random.Random(0),
+        )
+        assert len(result.referent_violations) >= 1
+
+    def test_verbatim_ratio_range(self) -> None:
+        """verbatim_ratio 始终在 [0.0, 1.0] 范围内。"""
+        result = run_postprocess(
+            question_text="What is shown?",
+            options=(
+                "A. A cat sits on the mat",
+                "B. A dog runs",
+                "C. A bird flies",
+                "D. A fish swims",
+            ),
+            answer="A",
+            source_texts=["A cat sits on the mat by the window."],
+            rng=random.Random(1),
+        )
+        assert 0.0 <= result.verbatim_ratio <= 1.0
+
+    def test_has_time_anchor_field(self) -> None:
+        """时间锚点字段正确填写。"""
+        result = run_postprocess(
+            question_text="What happens at 02:30?",
+            options=("A. X", "B. Y", "C. Z", "D. W"),
+            answer="C",
+            source_texts=["Some source text."],
+            rng=random.Random(5),
+        )
+        assert result.has_time_anchor is True