Update services/chain_filters.py

services/chain_filters.py

@@ -1,24 +1,28 @@
 from __future__ import annotations
 from typing import Dict, Any
+import re
 
-# よくあるチェーンの簡易ブラックリスト（小文字・空白/記号無視でマッチ）
+# よくあるチェーン（日本語含む）を拡張
 _CHAIN_KEYWORDS = {
-    # 和製チェーン
-    "マクドナルド", "mcdonald", "モスバーガー", "mosburger", "ケンタッキー", "kentuckyfriedchicken", "kfc",
+    # グローバル
+    "mcdonald", "burgerking", "subway", "wendy", "dominos", "pizzahut", "starbucks",
+    "bluebottlecoffee", "tullys", "paul", "pretamanger", "hardrockcafe", "kfc", "kentuckyfriedchicken",
+    # 国内大手（飲食）
+    "マクドナルド", "モスバーガー", "ケンタッキー", "フレッシュネスバーガー",
     "サイゼリヤ", "ガスト", "バーミヤン", "ジョナサン", "デニーズ", "ロイヤルホスト", "ココス", "やよい軒",
-    "松屋", "吉野家", "すき家", "リンガーハット", "丸亀製麺", "はなまるうどん",
+    "松屋", "吉野家", "すき家", "日高屋", "リンガーハット", "てんや",
+    "丸亀製麺", "はなまるうどん",
     "スシロー", "くら寿司", "はま寿司", "かっぱ寿司",
     "コメダ", "星乃珈琲", "サンマルク", "ドトール", "スターバックス", "スタバ",
-    "ココイチ", "cocoichibanya", "coCoichibanya",
-    # グローバル系
-    "burgerking", "subway", "wendy", "dominos", "pizzahut", "papa john", "chipotle", "tgifriday",
-    "hardrockcafe", "paul", "pretamanger", "starbucks", "bluebottlecoffee"
+    "ココイチ", "coco壱", "co co ichibanya", "cocoichibanya",
+    "鳥貴族", "磯丸水産", "和民", "塚田農場", "はなの舞",
+    # 今回問題に挙がった例
+    "つばめグリル", "けいすけ", "keisuke",
 }
 
 def _normalize(s: str) -> str:
-    import re
     s = (s or "").lower()
-    s = re.sub(r"[\s\-\_\.\&\(\)\'\"]+", "", s)
+    s = re.sub(r"[\s\-\_\.\&\(\)\'\"\u3000]+", "", s)
     return s
 
 def _match_chain(s: str) -> bool:
@@ -28,7 +32,7 @@ def _match_chain(s: str) -> bool:
     return any(k in ns for k in _CHAIN_KEYWORDS)
 
 def is_chain(name: str | None, tags: Dict[str, Any] | None = None) -> bool:
-    """OSM/Wiki由来の name / brand / operator / network を見てチェーンらしさを判定。"""
+    """name/brand/operator 等を見てチェーン判定。"""
     if _match_chain(name or ""):
         return True
     tags = tags or {}