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_language_terms.py

@@ -11,6 +11,48 @@ import re
 from typing import Any
 
 
+def replace_natural_language_term(text: str, raw: str, public: str) -> str:
+    """Replace one glossary term in prose only.
+
+    Identifiers and backtick spans stay as written. A trailing English plural
+    ``s`` is consumed with the English word, so it is not left after Chinese.
+    """
+
+    if not text or not raw:
+        return text
+    plural = "s?" if re.search(r"[A-Za-z]$", raw) and not raw.endswith("s") else ""
+    pattern = re.compile(rf"(?<![A-Za-z0-9_]){re.escape(raw)}{plural}(?![A-Za-z0-9_])")
+    parts = re.split(r"(`[^`]*`)", text)
+    return "".join(
+        part if index % 2 else pattern.sub(public, part)
+        for index, part in enumerate(parts)
+    )
+
+
+_LIFESPAN_ASSERTION = re.compile(
+    r"长寿|寿命长|短寿|寿命|longevity|lifespan|long life|short life",
+    re.IGNORECASE,
+)
+_LIFESPAN_EFFECT_ZH = "传统上与体质和恢复力有关，仅作参考"
+_LIFESPAN_EFFECT_EN = "Traditionally associated with constitution and recovery. Reference only."
+
+
+def strip_han_plural_s(text: str) -> str:
+    """Remove a Latin plural s left on Chinese after a glossary replace."""
+
+    return re.sub(r"([一-鿿])s\b", r"\1", text)
+
+
+def soften_lifespan_wording(text: str, language: str = "zh") -> str:
+    """Drop lifespan assertions from an effect cell. Yoga names are not passed here."""
+
+    if not text or not _LIFESPAN_ASSERTION.search(str(text)):
+        return text
+    if language == "en":
+        return _LIFESPAN_EFFECT_EN
+    return _LIFESPAN_EFFECT_ZH
+
+
 ZH_TERM_REPLACEMENTS: tuple[tuple[str, str], ...] = (
     ("Natural friends", "天然友星"),
     ("Natural enemies", "天然敌星"),
@@ -221,10 +263,22 @@ _ZH_LITERAL_REPLACEMENTS = tuple(
     if not re.fullmatch(r"[A-Za-z0-9_ /:-]+", raw)
 )
 _ZH_REGEX_REPLACEMENT_MAP = {raw: public for raw, public in _ZH_REGEX_REPLACEMENTS}
+
+
+def _zh_regex_body(raw: str) -> str:
+    body = re.escape(raw)
+    if re.search(r"[A-Za-z]$", raw) and not raw.endswith("s"):
+        body += "s?"
+    return body
+
+
 _ZH_REGEX_REPLACEMENT_PATTERN = re.compile(
-    r"(?<![A-Za-z])("
-    + "|".join(re.escape(raw) for raw, _public in sorted(_ZH_REGEX_REPLACEMENTS, key=lambda item: len(item[0]), reverse=True))
-    + r")(?![A-Za-z])"
+    r"(?<![A-Za-z0-9_])("
+    + "|".join(
+        _zh_regex_body(raw)
+        for raw, _public in sorted(_ZH_REGEX_REPLACEMENTS, key=lambda item: len(item[0]), reverse=True)
+    )
+    + r")(?![A-Za-z0-9_])"
 )
 
 _ZH_NAKSHATRA_GLOSSES = {
@@ -262,11 +316,23 @@ _ZH_NAKSHATRA_GLOSS_PATTERN = re.compile(
 )
 
 
+def _zh_regex_public(token: str) -> str:
+    if token in _ZH_REGEX_REPLACEMENT_MAP:
+        return _ZH_REGEX_REPLACEMENT_MAP[token]
+    if token.endswith("s") and token[:-1] in _ZH_REGEX_REPLACEMENT_MAP:
+        return _ZH_REGEX_REPLACEMENT_MAP[token[:-1]]
+    return token
+
+
 def _replace_zh_regex_terms(markdown: str) -> str:
-    return _ZH_REGEX_REPLACEMENT_PATTERN.sub(
-        lambda match: _ZH_REGEX_REPLACEMENT_MAP[match.group(1)],
-        markdown,
-    )
+    def apply(chunk: str) -> str:
+        return _ZH_REGEX_REPLACEMENT_PATTERN.sub(
+            lambda match: _zh_regex_public(match.group(1)),
+            chunk,
+        )
+
+    parts = re.split(r"(`[^`]*`)", markdown)
+    return "".join(part if index % 2 else apply(part) for index, part in enumerate(parts))
 
 
 def normalize_zh_markdown_terms(markdown: str) -> str:
@@ -321,7 +387,7 @@ def normalize_zh_markdown_terms(markdown: str) -> str:
     text = _normalize_zh_dasha_prose(text)
     text = _thicken_zh_dasha_density(text)
     text = _normalize_mula_gloss(_restore_zh_nakshatra_glosses(_collapse_duplicate_zh_parentheses(text)))
-    return text
+    return strip_han_plural_s(text)
 
 
 def _normalize_zh_bhava_factor_text(markdown: str) -> str: