diff --git a/arborist/qa/corpus_query.py b/arborist/qa/corpus_query.py
index f82dbef..a08afc8 100644
--- a/arborist/qa/corpus_query.py
+++ b/arborist/qa/corpus_query.py
@@ -192,7 +192,10 @@ def run_query(
     ts = _time.time()
     multi_route = bool(policy and policy.get("multi_route", False))
     if multi_route:
-        from arborist.qa.retrieval_routes import question_phrases
+        from arborist.qa.retrieval_routes import (
+            filter_by_title_relevance,
+            question_phrases,
+        )
         per_route_limit = top_k * 4
         body_hits = _safe_route(corpus, "fts_body", question, per_route_limit)
         title_hits = _safe_route(corpus, "fts_title", question, per_route_limit)
@@ -200,8 +203,6 @@ def run_query(
         phrase_hits = _safe_phrase_route(
             corpus, phrases, per_route_limit,
         ) if phrases else []
-        # core_keyword needs qtokens; reuse the title_query_tokens helper
-        # since legacy query() does the same thing.
         from arborist.qa.query import _title_query_tokens
         qtokens = list(_title_query_tokens(question))
         core_hits = _safe_core_route(
@@ -210,6 +211,22 @@ def run_query(
         hits = _merge_routes_min_bm25(
             body_hits, title_hits, phrase_hits, core_hits,
         )
+        # 5-accept-path filter from arborist.qa.retrieval_routes —
+        # gates the merged set on title-overlap / synonym / TFIDF-core
+        # match / verbatim-phrase match / hyphen-fold anchor. Without
+        # this, multi-route over-recalls on noisy title overlaps (e.g.
+        # "East Asia" outranks "Nineteen Eighty-Four" for the Orwell
+        # phrase query). core_match_roots and phrase_match_roots are
+        # passed through so accept-paths 2 + 4 fire on docs that
+        # surfaced via those routes even when titles miss.
+        core_match_roots = {h.document_root for h in core_hits}
+        phrase_match_roots = {h.document_root for h in phrase_hits}
+        hits = filter_by_title_relevance(
+            hits, question,
+            core_match_roots=core_match_roots,
+            phrase_match_roots=phrase_match_roots,
+            fallback_top_n=top_k,
+        )
     else:
         try:
             hits = corpus.fts_body(question, limit=top_k * 4)