| |
| |
| |
| |
| """ |
| Convert WS BIO dataset to CoNLL-U format and compute statistics. |
| |
| Reads udd-ws-v1.1-{train,dev,test}.txt (BIO format) and: |
| 1. Converts to CoNLL-U: udd-ws-v1.1-{train,dev,test}.conllu |
| 2. Prints statistics matching the style of statistics.py |
| |
| CoNLL-U format: each word is a token, multi-syllable words have |
| syllables joined by space in FORM field (Vietnamese UD convention). |
| """ |
|
|
| from collections import Counter |
| from os.path import dirname, isfile, join |
|
|
|
|
| def parse_bio_file(filepath): |
| """Parse BIO file into sentences with metadata and word-level tokens. |
| |
| Returns list of dicts with keys: sent_id, text, words, domain. |
| Each word is a string (syllables joined by space for multi-syllable words). |
| """ |
| sentences = [] |
| current = {"sent_id": "", "text": "", "syllables": [], "tags": []} |
|
|
| with open(filepath, "r", encoding="utf-8") as f: |
| for line in f: |
| line = line.rstrip("\n") |
| if line.startswith("# sent_id = "): |
| current["sent_id"] = line.split("= ", 1)[1] |
| continue |
| if line.startswith("# text = "): |
| current["text"] = line.split("= ", 1)[1] |
| continue |
| if line.startswith("#"): |
| continue |
| if not line: |
| if current["syllables"]: |
| words = bio_to_words(current["syllables"], current["tags"]) |
| domain = sent_id_to_domain(current["sent_id"]) |
| sentences.append({ |
| "sent_id": current["sent_id"], |
| "text": current["text"], |
| "words": words, |
| "domain": domain, |
| }) |
| current = {"sent_id": "", "text": "", "syllables": [], "tags": []} |
| continue |
| parts = line.split("\t") |
| if len(parts) == 2: |
| current["syllables"].append(parts[0]) |
| current["tags"].append(parts[1]) |
|
|
| if current["syllables"]: |
| words = bio_to_words(current["syllables"], current["tags"]) |
| domain = sent_id_to_domain(current["sent_id"]) |
| sentences.append({ |
| "sent_id": current["sent_id"], |
| "text": current["text"], |
| "words": words, |
| "domain": domain, |
| }) |
|
|
| return sentences |
|
|
|
|
| def bio_to_words(syllables, tags): |
| """Convert syllable-level BIO tags to word list.""" |
| words = [] |
| current = [] |
| for syl, tag in zip(syllables, tags): |
| if tag == "B-W": |
| if current: |
| words.append(" ".join(current)) |
| current = [syl] |
| else: |
| current.append(syl) |
| if current: |
| words.append(" ".join(current)) |
| return words |
|
|
|
|
| def sent_id_to_domain(sent_id): |
| if sent_id.startswith("vlc-"): |
| return "legal" |
| elif sent_id.startswith("uvn-"): |
| return "news" |
| elif sent_id.startswith("uvw-"): |
| return "wikipedia" |
| elif sent_id.startswith("uvb-f-"): |
| return "fiction" |
| elif sent_id.startswith("uvb-n-"): |
| return "non-fiction" |
| return "unknown" |
|
|
|
|
| def write_conllu(sentences, filepath): |
| """Write sentences to CoNLL-U format.""" |
| with open(filepath, "w", encoding="utf-8") as f: |
| for sent in sentences: |
| f.write(f"# sent_id = {sent['sent_id']}\n") |
| f.write(f"# text = {sent['text']}\n") |
| for i, word in enumerate(sent["words"], 1): |
| |
| f.write(f"{i}\t{word}\t_\t_\t_\t_\t_\t_\t_\t_\n") |
| f.write("\n") |
|
|
|
|
| def compute_statistics(sentences): |
| """Compute statistics from parsed sentences.""" |
| stats = {} |
|
|
| stats["num_sentences"] = len(sentences) |
| stats["num_words"] = sum(len(s["words"]) for s in sentences) |
| stats["num_syllables"] = sum( |
| sum(len(w.split()) for w in s["words"]) for s in sentences |
| ) |
|
|
| |
| sent_lengths = [len(s["words"]) for s in sentences] |
| stats["avg_sent_length"] = sum(sent_lengths) / len(sent_lengths) if sent_lengths else 0 |
| stats["min_sent_length"] = min(sent_lengths) if sent_lengths else 0 |
| stats["max_sent_length"] = max(sent_lengths) if sent_lengths else 0 |
|
|
| |
| sent_syl_lengths = [sum(len(w.split()) for w in s["words"]) for s in sentences] |
| stats["avg_sent_syl_length"] = sum(sent_syl_lengths) / len(sent_syl_lengths) if sent_syl_lengths else 0 |
|
|
| |
| word_syl_counts = Counter() |
| for s in sentences: |
| for w in s["words"]: |
| n_syls = len(w.split()) |
| word_syl_counts[n_syls] += 1 |
| stats["word_syl_counts"] = word_syl_counts |
|
|
| |
| domain_counts = Counter(s["domain"] for s in sentences) |
| stats["domain_counts"] = domain_counts |
|
|
| return stats |
|
|
|
|
| def print_statistics(name, stats): |
| """Print statistics in the same format as statistics.py.""" |
| print("=" * 60) |
| print(f" {name}") |
| print("=" * 60) |
|
|
| print("\n## Basic Statistics") |
| print(f" Sentences: {stats['num_sentences']:>10,}") |
| print(f" Words: {stats['num_words']:>10,}") |
| print(f" Syllables: {stats['num_syllables']:>10,}") |
| print(f" Avg word/sent: {stats['avg_sent_length']:>10.2f}") |
| print(f" Avg syl/sent: {stats['avg_sent_syl_length']:>10.2f}") |
| print(f" Avg syl/word: {stats['num_syllables']/stats['num_words']:>10.2f}") |
| print(f" Min word/sent: {stats['min_sent_length']:>10}") |
| print(f" Max word/sent: {stats['max_sent_length']:>10}") |
|
|
| print("\n## Word Length Distribution (by syllable count)") |
| print(f" {'Syllables':<12} {'Count':>10} {'Percent':>8}") |
| print(" " + "-" * 32) |
| total_words = stats["num_words"] |
| for n_syls in sorted(stats["word_syl_counts"]): |
| count = stats["word_syl_counts"][n_syls] |
| pct = count / total_words * 100 |
| print(f" {n_syls:<12} {count:>10,} {pct:>7.2f}%") |
|
|
| print("\n## Domain Distribution") |
| print(f" {'Domain':<15} {'Count':>10} {'Percent':>8}") |
| print(" " + "-" * 35) |
| total_sents = stats["num_sentences"] |
| for domain in ["legal", "news", "wikipedia", "fiction", "non-fiction"]: |
| count = stats["domain_counts"].get(domain, 0) |
| pct = count / total_sents * 100 |
| print(f" {domain:<15} {count:>10,} {pct:>7.2f}%") |
|
|
| print() |
|
|
|
|
| def main(): |
| base_dir = dirname(dirname(__file__)) |
|
|
| splits = { |
| "train": "udd-ws-v1.1-train.txt", |
| "dev": "udd-ws-v1.1-dev.txt", |
| "test": "udd-ws-v1.1-test.txt", |
| } |
|
|
| all_stats = {} |
|
|
| for split_name, filename in splits.items(): |
| bio_path = join(base_dir, filename) |
| if not isfile(bio_path): |
| print(f"WARNING: {bio_path} not found, skipping") |
| continue |
|
|
| |
| print(f"Reading {filename}...") |
| sentences = parse_bio_file(bio_path) |
|
|
| |
| conllu_path = bio_path.replace(".txt", ".conllu") |
| write_conllu(sentences, conllu_path) |
| print(f" → {conllu_path}") |
|
|
| |
| stats = compute_statistics(sentences) |
| all_stats[split_name] = stats |
|
|
| |
| for split_name, stats in all_stats.items(): |
| print_statistics(f"udd-ws-v1.1 — {split_name}", stats) |
|
|
| |
| if all_stats: |
| combined = { |
| "num_sentences": sum(s["num_sentences"] for s in all_stats.values()), |
| "num_words": sum(s["num_words"] for s in all_stats.values()), |
| "num_syllables": sum(s["num_syllables"] for s in all_stats.values()), |
| "min_sent_length": min(s["min_sent_length"] for s in all_stats.values()), |
| "max_sent_length": max(s["max_sent_length"] for s in all_stats.values()), |
| "word_syl_counts": Counter(), |
| "domain_counts": Counter(), |
| } |
| for s in all_stats.values(): |
| combined["word_syl_counts"] += s["word_syl_counts"] |
| combined["domain_counts"] += s["domain_counts"] |
| combined["avg_sent_length"] = combined["num_words"] / combined["num_sentences"] |
| combined["avg_sent_syl_length"] = combined["num_syllables"] / combined["num_sentences"] |
|
|
| print_statistics("udd-ws-v1.1 — TOTAL", combined) |
|
|
| |
| print("=" * 60) |
| print(" Summary") |
| print("=" * 60) |
| print(f"\n {'Split':<8} {'Sentences':>10} {'Words':>10} {'Syllables':>12}") |
| print(" " + "-" * 42) |
| for split_name, stats in all_stats.items(): |
| print(f" {split_name:<8} {stats['num_sentences']:>10,} {stats['num_words']:>10,} {stats['num_syllables']:>12,}") |
| print(f" {'TOTAL':<8} {combined['num_sentences']:>10,} {combined['num_words']:>10,} {combined['num_syllables']:>12,}") |
| print() |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
