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TARGET = ".data/speeches.vert.shuffled"
import os
import re
from typing import Dict
import jsonlines
from tqdm import tqdm
def process_vert_format(vert_content: str) -> Dict[str, str]:
doc_pattern = re.compile(r'<doc[^>]*>.*?</doc>', re.DOTALL)
# Pattern to match document boundaries and extract metadata
metadata_pattern = re.compile(
r'<doc id="([^"]*)"\s+speaker="([^"]*)"\s+year="([^"]*)"\s+date="([^"]*)"\s+title="([^"]*)"\s+office="([^"]*)"\s+occasion="([^"]*)"\s+medium="([^"]*)"\s+source="([^"]*)"\s+link="([^"]*)"\s+altsource="([^"]*)"\s+status="([^"]*)"\s+notes="([^"]*)">'
)
block_pattern = re.compile(r'<block[^>]*>.*?</block>', re.DOTALL)
# Pattern to remove whitespace before punctuation
ws_before_punct = re.compile(r'\s+([.,!?:;])')
# Find all documents
documents = re.findall(doc_pattern, vert_content)
processed_documents = {}
for doc in tqdm(documents):
# Extract metadata
metadata_match = re.search(metadata_pattern, doc)
if metadata_match:
doc_id = metadata_match.group(1)
speaker = metadata_match.group(2)
year = metadata_match.group(3)
date = metadata_match.group(4)
title = metadata_match.group(5)
office = metadata_match.group(6)
occasion = metadata_match.group(7)
medium = metadata_match.group(8)
source = metadata_match.group(9)
link = metadata_match.group(10)
altsource = metadata_match.group(11)
status = metadata_match.group(12)
notes = metadata_match.group(13)
metadata_str = (f"Řečník: {speaker}, "
f"Rok: {year}, "
f"Datum: {date}, "
f"Název: {title}, "
f"Úřad: {office}, "
f"Příležitost: {occasion}, ")
else:
raise ValueError("Metadata not found in document")
for bid, block in enumerate(re.findall(block_pattern, doc)):
# remove tags from each line, and join text
tokens = [line.split("\t")[0].strip() for line in block.split("\n") if line.strip() != ""]
doc_text = " ".join(tokens)
# remove any text with <...> tag
doc_text = re.sub(r'<[^>]*>', '', doc_text)
# replace more than one space with one space
doc_text = re.sub(r'\s+', ' ', doc_text).strip()
# remove whitespace before ., !, ?
doc_text = re.sub(ws_before_punct, r'\1', doc_text)
# - sometimes lines in oral are empty? e.g. 08A009N // REMOVE THESE LINES
if doc_text.strip() == "":
continue
processed_documents[f"{doc_id}_{bid}"] = metadata_str + "\n" + doc_text
return processed_documents
# Read the content from the file
with open(TARGET, "r") as f:
vert_content = f.read()
# Process the content
processed_documents = process_vert_format(vert_content)
# write all splits into same json file in .data/hf_dataset/cnc_fictree/test.jsonl
OF = ".data/hf_dataset/cnc_prez_prejavy/test.jsonl"
os.makedirs(os.path.dirname(OF), exist_ok=True)
with jsonlines.open(OF, "w") as writer:
for doc_id, doc in list(processed_documents.items()):
writer.write({"text": doc, "id": doc_id})
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