fix(report): project annual sections and thicken dasha reading

完整数据版第二轮。年运章写出资料包里已有的节，没有数据的不新算。大运解释补回可能段落。瑜伽作用不再断言寿命。术语替换不进标识符。罗睺和计都不写守护第未列出宫。未合入 staging。

scripts/pl9_full_data_export.py

@@ -95,9 +95,17 @@ def _sanitize_pl9_ai_density_markdown(markdown: str, title: str = "印度占星
     """Keep the parity volume's facts while removing internal-only labels."""
 
     try:
-        from pl9_language_terms import normalize_zh_markdown_terms
+        from pl9_language_terms import (
+            normalize_zh_markdown_terms,
+            replace_natural_language_term,
+            strip_han_plural_s,
+        )
     except ModuleNotFoundError:  # pragma: no cover - package import compatibility
-        from scripts.pl9_language_terms import normalize_zh_markdown_terms
+        from scripts.pl9_language_terms import (
+            normalize_zh_markdown_terms,
+            replace_natural_language_term,
+            strip_han_plural_s,
+        )
 
     text = _sanitize_pl9_public_markdown(markdown)
     replacements = {
@@ -141,9 +149,6 @@ def _sanitize_pl9_ai_density_markdown(markdown: str, title: str = "印度占星
         "functional_role_not_returned": "功能属性未单独返回",
         "natural_benefic": "自然吉星",
         "natural_malefic": "自然凶星",
-        "functional_benefic": "功能吉星",
-        "functional_malefic": "功能凶星",
-        "functional_neutral": "功能中性",
         "current_dasha": "当前 Dasha",
         "birth_balance": "出生余额",
         "Cycle / phase": "周期 / 阶段",
@@ -196,6 +201,12 @@ def _sanitize_pl9_ai_density_markdown(markdown: str, title: str = "印度占星
     }
     for raw, public in replacements.items():
         text = text.replace(raw, public)
+    for raw, public in (
+        ("functional_benefic", "功能吉星"),
+        ("functional_malefic", "功能凶星"),
+        ("functional_neutral", "功能中性"),
+    ):
+        text = replace_natural_language_term(text, raw, public)
     text = re.sub(
         r"\n## Bhavesh House-Lord Interpretations\n\n.*?(?=\n## |\Z)",
         "\n",
@@ -218,7 +229,7 @@ def _sanitize_pl9_ai_density_markdown(markdown: str, title: str = "印度占星
     text = text.replace("Planetary", "行星")
     text = text.replace("Planets", "行星")
     text = text.replace("Planet", "行星")
-    text = text.replace("Sign", "星座")
+    text = replace_natural_language_term(text, "Sign", "星座")
     text = text.replace("Degree in sign", "落座度数")
     text = text.replace("Degree", "度数")
     text = text.replace("Longitude", "黄经")
@@ -451,12 +462,12 @@ def _sanitize_pl9_ai_density_markdown(markdown: str, title: str = "印度占星
         "weak": "弱",
         "medium": "中等",
         "strong": "强",
-        "house condition": "宫位条件",
         "house ": "第",
-        " condition": "宫条件",
     }
+    text = replace_natural_language_term(text, "house condition", "宫位条件")
     for raw, public in zh_heading_repairs.items():
         text = text.replace(raw, public)
+    text = replace_natural_language_term(text, " condition", "宫条件")
     zh_public_key_repairs = {
         "mangal_dosha": "火星婚姻煞",
         "kaal_sarp_dosha": "时蛇煞",
@@ -506,7 +517,7 @@ def _sanitize_pl9_ai_density_markdown(markdown: str, title: str = "印度占星
             ]
         )
         text = re.sub(r"^#\s+.*$", summary, text, count=1, flags=re.MULTILINE)
-    return text + "\n"
+    return strip_han_plural_s(text) + "\n"
 
 
 
@@ -1001,7 +1012,8 @@ def _sanitize_pl9_ai_density_markdown_en(markdown: str, title: str = "Vedic Astr
         "王权/事业": "authority/career",
         "天象格局": "configuration",
         "子女/创造": "children/creativity",
-        "寿命/健康": "longevity/health",
+        "体质参考": "constitution reference",
+        "寿命/健康": "constitution reference",
         "愿望/收益": "desire/gains",
         "解脱/内在": "moksha/inner life",
         "贵人/助力": "patronage/support",
@@ -1494,10 +1506,18 @@ def _render_pl9_ai_density_raw_data_markdown_en(packet: dict) -> str:
         stripped = value.strip()
         translated = EFFECTS_EN.get(stripped)
         if translated:
-            return translated
+            try:
+                from pl9_language_terms import soften_lifespan_wording
+            except ModuleNotFoundError:  # pragma: no cover
+                from scripts.pl9_language_terms import soften_lifespan_wording
+            return soften_lifespan_wording(translated, "en")
         # 已是英文短语（无 CJK）时原样透传，避免被误当占位删掉。
         if re.search(r"[A-Za-z]", stripped) and not re.search(r"[\u4e00-\u9fff]", stripped):
-            return stripped
+            try:
+                from pl9_language_terms import soften_lifespan_wording
+            except ModuleNotFoundError:  # pragma: no cover
+                from scripts.pl9_language_terms import soften_lifespan_wording
+            return soften_lifespan_wording(stripped, "en")
         return ""
 
     def table(headers: list[str], rows: list[list[Any]]) -> str: