Issue #32 cleanup — drop the last 5 mis-oriented vocab pairs

Two small fixes after the LLM-vision pass:

1. merge_pdf_into_book.py — when the LLM classifies an image as 'hybrid'
   but extracts zero pairs (e.g., a conjugation table whose only English
   text is on the section header that was excluded by the prompt rules),
   respect that decision instead of falling through to the bbox/heuristic
   pipeline. Previously: 1 chapter-2 estar conjugation table generated
   4 bad pairs from the heuristic fallback.

2. fix_vocab.py language_score — recognize Spanish present-perfect
   ('he tenido', 'He andado por este pueblo') as Spanish. The classifier
   was treating the auxiliary 'he'/'has'/'ha' as English subject pronouns,
   producing false-positive mis-orientation flags on 4 chapter-15/20/23
   present-perfect example tables.

Result: mis-oriented vocab pairs across the book go from 5 → 0.
textbookDataVersion bumped to 14.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Conjuga/Scripts/textbook/fix_vocab.py

@@ -46,6 +46,9 @@ SPANISH_ARTICLES = {"el", "la", "los", "las", "un", "una", "unos", "unas"}
 ENGLISH_STARTERS = {"the", "a", "an", "to", "my", "his", "her", "our", "their"}
 
 
+HABER_FORMS = {"he", "has", "ha", "hemos", "habéis", "han"}
+
+
 def language_score(s: str) -> "tuple[int, int]":
     """Return (es_score, en_score) for a string."""
     es = 0
@@ -56,9 +59,17 @@ def language_score(s: str) -> "tuple[int, int]":
     if not words:
         return (es, en)
     first = words[0].strip(",.;:")
-    if first in SPANISH_ARTICLES:
+    second = words[1].strip(",.;:") if len(words) > 1 else ""
+    # Spanish present-perfect ("he tenido", "Ha andado") starts with a haber
+    # form followed by an -ado/-ido past participle. Recognise this pattern
+    # before the bare-pronoun check so "he" isn't mistaken for English "he".
+    if first in HABER_FORMS and (
+        second.endswith(("ado", "ido", "to", "cho", "sto", "esto"))
+    ):
+        es += 3
+    elif first in SPANISH_ARTICLES:
         es += 2
-    if first in ENGLISH_STARTERS:
+    elif first in ENGLISH_STARTERS:
         en += 2
     # Spanish-likely endings on later words
     for w in words: