Files
unredact/scripts/build_word_lists.py
T
Alex-GilbertandClaude Opus 4.6 e6b38ebc6a feat: add word frequency filtering with vocabulary size control
Sort word lists by Google Books frequency (most common first).
Add vocabulary dropdown (Common/Standard/Extended/Full) to word
mode UI that controls how many words are searched.

Co-Authored-By: Claude Opus 4.6 <[email protected]>
2026-02-23 14:10:08 -06:00

212 lines
7.0 KiB
Python

"""Build word list files (nouns, plurals, adjectives) from WordNet via NLTK.
Usage:
python scripts/build_word_lists.py [--data-dir PATH]
Extracts nouns and adjectives from WordNet, generates plural forms using
irregular mappings from Wiktionary/GitHub and standard English rules, then
sorts all lists by word frequency (Google Books corpus) and writes three
files to unredact/data/:
- nouns.txt (singular nouns, sorted by frequency)
- nouns_plural.txt (corresponding plural for each noun, same order)
- adjectives.txt (adjectives, sorted by frequency)
"""
import argparse
import csv
import io
import re
import urllib.error
import urllib.request
from pathlib import Path
import nltk
OUTPUT_DIR = Path(__file__).parent.parent / "unredact" / "data"
IRREGULAR_PLURALS_URL = (
"https://raw.githubusercontent.com/djstrong/nouns-with-plurals/master/noun.csv"
)
FREQUENCY_URL = (
"https://raw.githubusercontent.com/hackerb9/gwordlist/master/frequency-alpha-alldicts.txt"
)
# Regex: only lowercase alpha, no digits/hyphens/underscores/spaces
VALID_WORD = re.compile(r"^[a-z]+$")
def extract_wordnet_words(pos_tags: list[str]) -> list[str]:
"""Extract unique lowercase words from WordNet for given POS tags.
Only words matching [a-z]+ are included.
"""
from nltk.corpus import wordnet as wn
words: set[str] = set()
for pos in pos_tags:
for lemma in wn.all_lemma_names(pos=pos):
word = lemma.lower()
if VALID_WORD.match(word):
words.add(word)
return sorted(words)
def download_irregular_plurals() -> dict[str, str]:
"""Download irregular plural mappings from GitHub.
Returns: {singular: plural} dict, filtered to [a-z]+ words only.
"""
print(f"Downloading irregular plurals from {IRREGULAR_PLURALS_URL}...")
try:
response = urllib.request.urlopen(IRREGULAR_PLURALS_URL)
except (urllib.error.URLError, OSError) as exc:
print(f" WARNING: failed to download irregular plurals: {exc}")
print(" Continuing with rule-based pluralization only.")
return {}
text = response.read().decode("utf-8")
mapping: dict[str, str] = {}
reader = csv.reader(io.StringIO(text))
for row in reader:
if len(row) < 2:
continue
singular = row[0].strip().lower()
plural = row[1].strip().lower()
if VALID_WORD.match(singular) and VALID_WORD.match(plural):
mapping[singular] = plural
print(f" -> loaded {len(mapping)} irregular plural mappings")
return mapping
def pluralize(word: str) -> str:
"""Apply standard English pluralization rules to a word."""
if word.endswith("fe"):
return word[:-2] + "ves"
if word.endswith("f"):
return word[:-1] + "ves"
if word.endswith(("s", "x", "z")) or word.endswith(("sh", "ch")):
return word + "es"
if word.endswith("y") and len(word) >= 2 and word[-2] not in "aeiou":
return word[:-1] + "ies"
return word + "s"
def generate_plurals(nouns: list[str], irregulars: dict[str, str]) -> list[str]:
"""Generate plural form for each noun.
Uses irregular mapping if available, otherwise applies rules.
"""
plurals: list[str] = []
for noun in nouns:
if noun in irregulars:
plurals.append(irregulars[noun])
else:
plurals.append(pluralize(noun))
return plurals
def download_frequency_ranks() -> dict[str, int]:
"""Download word frequency rankings from Google Books corpus.
Returns: {word: rank} dict where rank 1 = most common.
"""
print(f"Downloading frequency data from hackerb9/gwordlist...")
try:
response = urllib.request.urlopen(FREQUENCY_URL)
except (urllib.error.URLError, OSError) as exc:
print(f" WARNING: failed to download frequency data: {exc}")
print(" Words will be sorted alphabetically instead.")
return {}
text = response.read().decode("utf-8")
ranks: dict[str, int] = {}
for line in text.splitlines():
if line.startswith("#") or not line.strip():
continue
parts = line.split()
if len(parts) >= 2:
rank = int(parts[0])
word = parts[1].lower()
if word not in ranks:
ranks[word] = rank
print(f" -> loaded {len(ranks)} word frequency rankings")
return ranks
def sort_by_frequency(words: list[str], freq_ranks: dict[str, int]) -> list[str]:
"""Sort words by frequency rank. Unranked words go to the end."""
max_rank = len(freq_ranks) + 1
return sorted(words, key=lambda w: freq_ranks.get(w, max_rank))
def write_word_list(path: Path, words: list[str]) -> None:
"""Write a word list, one word per line."""
path.write_text("\n".join(words) + "\n")
print(f"Wrote {len(words)} words to {path}")
def main():
parser = argparse.ArgumentParser(
description="Build word list files from WordNet (nouns, adjectives, plurals)"
)
parser.add_argument(
"--data-dir",
type=Path,
default=OUTPUT_DIR,
help="Directory to write output files (default: unredact/data/)",
)
args = parser.parse_args()
args.data_dir.mkdir(parents=True, exist_ok=True)
# Ensure WordNet corpus is available
nltk.download("wordnet", quiet=True)
# Extract nouns (POS 'n')
print("Extracting nouns from WordNet...")
nouns = extract_wordnet_words(["n"])
print(f" -> {len(nouns)} nouns")
# Extract adjectives (POS 'a' for adjective, 's' for satellite adjective)
print("Extracting adjectives from WordNet...")
adjectives = extract_wordnet_words(["a", "s"])
print(f" -> {len(adjectives)} adjectives")
# Download irregular plural mappings
irregulars = download_irregular_plurals()
# Download frequency data
freq_ranks = download_frequency_ranks()
# Sort by frequency (most common first)
if freq_ranks:
print("Sorting by frequency...")
nouns_sorted = sort_by_frequency(nouns, freq_ranks)
adjectives_sorted = sort_by_frequency(adjectives, freq_ranks)
# Build noun->plural mapping, then reorder plurals to match sorted nouns
noun_to_plural = dict(zip(nouns, generate_plurals(nouns, irregulars)))
plurals_sorted = [noun_to_plural[n] for n in nouns_sorted]
ranked_nouns = sum(1 for n in nouns_sorted if n in freq_ranks)
ranked_adj = sum(1 for a in adjectives_sorted if a in freq_ranks)
print(f" -> {ranked_nouns}/{len(nouns_sorted)} nouns have frequency data")
print(f" -> {ranked_adj}/{len(adjectives_sorted)} adjectives have frequency data")
else:
nouns_sorted = nouns
adjectives_sorted = adjectives
plurals_sorted = generate_plurals(nouns, irregulars)
# Write output files
write_word_list(args.data_dir / "nouns.txt", nouns_sorted)
write_word_list(args.data_dir / "nouns_plural.txt", plurals_sorted)
write_word_list(args.data_dir / "adjectives.txt", adjectives_sorted)
print("Done.")
if __name__ == "__main__":
main()