convert_ksk.py

TARGET = ".data/ksk-dopisy.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+signatura="([^"]*)"\s+archiv="([^"]*)"\s+pispohl="([^"]*)"\s+pisvek="([^"]*)"\s+pisvzdel="([^"]*)"\s+pispobyt="([^"]*)"\s+pister="([^"]*)"\s+vztah="([^"]*)"\s+adrpohl="([^"]*)"\s+adrvek="([^"]*)"\s+adrvzdel="([^"]*)"\s+rok="([^"]*)"\s+forma="([^"]*)">'
    )
    block_pattern = re.compile(r'<block[^>]*>.*?</block>', re.DOTALL)
    note_pattern = re.compile(r'<note text="([^"]*)"/>\s*@')

    # 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:
            # r'<doc id="([^"]*)".+?rok="([^"]*)".+?misto="([^"]*)" sidlotyp="([^"]*)".+?tema="([^"]*)" pocetml="([^"]*)"')
            doc_id = metadata_match.group(1)
            signatura = metadata_match.group(2)
            archiv = metadata_match.group(3)
            pispohl = metadata_match.group(4)
            pisvek = metadata_match.group(5)
            pisvzdel = metadata_match.group(6)
            pispobyt = metadata_match.group(7)
            pister = metadata_match.group(8)
            vztah = metadata_match.group(9)
            adrpohl = metadata_match.group(10)
            adrvek = metadata_match.group(11)
            adrvzdel = metadata_match.group(12)
            rok = metadata_match.group(13)
            forma = metadata_match.group(14)

            pispohl = "Žena" if pispohl == "F" else ("Muž" if pispohl == "M" else pispohl)
            adrpohl = "Žena" if adrpohl == "F" else ("Muž" if adrpohl == "M" else adrpohl)

            metadata_str = (f"Pohlaví pisatele: {pispohl}, "
                            f"Pobyt pisatele: {pispobyt}, "
                            f"Počet dětí pisatele: {pister}, "
                            f"Pohlaví adresáta: {adrpohl}, "
                            f"Rok: {rok}, ")
        else:
            raise ValueError("Metadata not found in document")

        for bid, block in enumerate(re.findall(block_pattern, doc)):
            # replace notes followed by tags in the document just with notes
            block = note_pattern.sub(r'@\1@', block)

            # 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_ksk/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})