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>
This commit is contained in:
Trey T
2026-05-03 18:52:53 -05:00
parent f368c24ad6
commit 05a0cc0d17
5 changed files with 21 additions and 223 deletions
+13 -2
View File
@@ -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:
@@ -307,10 +307,13 @@ def main() -> None:
# Choose pair source. For reference_only (Spanish-only tables)
# we deliberately produce no cards — the UI will fall back to
# rendering the flat OCR lines as a reference list.
if llm_kind == "reference_only":
# rendering the flat OCR lines as a reference list. Same for
# hybrid images where the LLM determined no genuine pair rows
# exist (e.g. estar conjugations with English glosses on the
# header row only).
if llm_kind == "reference_only" or (llm_kind == "hybrid" and not llm_pairs):
cards_for_block = []
pair_source = "llm-reference"
pair_source = "llm-no-pairs"
elif llm_pairs:
cards_for_block = [
{"front": p["es"], "back": p["en"]}