src/preprocess/ENLP.py

from utils import parse, read_json_file, write_jsonl_file
import os

def get_prefix_lengths(lengths):
    prefix_lengths = [0]
    for length in lengths:
        prefix_lengths.append(prefix_lengths[-1] + length)

    return prefix_lengths


def custom_join(tokens, start, end):
    joined_str = ""
    for i in range(start, end):
        joined_str += tokens[i]
        if (
            i == end - 1
            or tokens[i + 1] in ["-", ","]
            or tokens[i + 1].startswith("'")
            or tokens[i] == "-"
        ):
            continue
        joined_str += " "

    if joined_str.count('"') > 1:
        start = joined_str.index('"')
        end = joined_str[start + 1 :].index('"')
        joined_str = (
            joined_str[: start + 1]
            + joined_str[start + 1 :][:end].strip()
            + joined_str[start + 1 :][end:]
        )

    return joined_str


def parse_characters(utterance, tokens, character_entities):
    utterance_char_idx = 0
    characters = []
    for sent_idx, sent in enumerate(character_entities):
        prefix_lengths = get_prefix_lengths(map(len, tokens[sent_idx]))
        for character in sent:
            span = ", ".join(character[2:])
            scan_length = prefix_lengths[character[0]]
            start = utterance_char_idx

            while scan_length >= 0 and start < len(utterance):
                if scan_length == 0 and utterance[start] != " ":
                    break

                if utterance[start] != " ":
                    scan_length -= 1

                start += 1

            scan_length = prefix_lengths[character[1]] - prefix_lengths[character[0]]
            end = start

            while scan_length > 0 and end < len(utterance):
                if utterance[end] != " ":
                    scan_length -= 1

                end += 1

            characters.append({"value": span, "start": start, "end": end})
            # print(utterance)
            # print(tokens)
            # print(character_entities)
            # print(
            #     utterance_char_idx,
            #     start,
            #     end,
            #     utterance[start:end],
            #     tokens[sent_idx][character[0] : character[1]],
            #     custom_join(tokens[sent_idx], character[0], character[1]),
            # )

            if utterance[start:end] == "Emily- noooo":
                continue

            assert utterance[start:end] == custom_join(
                tokens[sent_idx], character[0], character[1]
            )

        # update utterance char idx
        scan_length = prefix_lengths[-1]
        while scan_length >= 0 and utterance_char_idx < len(utterance):
            if scan_length == 0 and utterance[utterance_char_idx] != " ":
                break

            if utterance[utterance_char_idx] != " ":
                scan_length -= 1

            utterance_char_idx += 1

    return characters


def preprocess(args, split):
    input_file = os.path.join(args.input_dir, f"character-identification-{split}.json")

    if split == "trn":
        split = "train"
    elif split == "tst":
        split = "test"

    output_file = os.path.join(args.output_dir, f"{split}.jsonl")

    episodes = read_json_file(input_file)["episodes"]

    processed_data = []
    for episode in episodes:
        scenes = episode["scenes"]
        for scene in scenes:
            utterances = scene["utterances"]
            dialog = {
                "turn": "multi",
                "locale": "en",
                "dialog": [],
            }

            roles = ["#GENERAL#", "#OTHER#", "#ALL#"]
            # labels = set()
            for example in utterances:
                utterance = example["transcript"]
                tokens = example["tokens"]
                character_entities = example["character_entities"]

                characters = parse_characters(utterance, tokens, character_entities)
                dialog["dialog"].append(
                    {
                        "roles": example["speakers"],
                        "utterance": utterance,
                        "characters": characters,
                    }
                )

                roles += example["speakers"]

                # for character in characters:
                #     labels.add(character["value"])

            # assert not len(labels - set(roles)), f"\n{sorted(labels)} \n {sorted(set(roles))}"
            dialog["knowledge"] = {"type": "lsit", "value": sorted(roles)}
            processed_data.append(dialog)

    write_jsonl_file(processed_data, output_file)


if __name__ == "__main__":
    args = parse()
    preprocess(args, "trn")
    preprocess(args, "dev")
    preprocess(args, "tst")