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""" |
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Adds clue/cluewsc2020 samples to xwinograd |
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From: https://gist.github.com/jordiclive/26506ea7e897ad8270f9e793bdc285b5 |
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""" |
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import json |
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import datasets |
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import pandas as pd |
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from datasets import load_dataset |
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def find_pronoun(x): |
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pronoun = x["target"]["span2_text"] |
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indices = [x["target"]["span2_index"], x["target"]["span2_index"] + len(pronoun)] |
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return [pronoun, indices, list(pronoun)] |
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def find_switch(x): |
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pronoun = x["target"]["span1_text"] |
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indices = [x["target"]["span1_index"], x["target"]["span1_index"] + len(pronoun)] |
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if x["label"] == 1: |
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label = False |
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else: |
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label = True |
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return [pronoun, indices, list(pronoun), label] |
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def convert_to_format(df): |
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df["pronoun"] = df.apply(find_pronoun, axis=1) |
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df["toks"] = df["text"].apply(lambda x: list(x)) |
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df["switch"] = df.apply(find_switch, axis=1) |
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df.reset_index(inplace=True, drop=True) |
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lang = [] |
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original = [] |
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o_text = [] |
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sent = [] |
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toks = [] |
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pronoun = [] |
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switch = [] |
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df["pronoun_to_replace"] = df["target"].apply(lambda x: x["span2_text"]) |
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for i, df_text in df.groupby(["text", "pronoun_to_replace"]): |
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if len(df_text) == 1: |
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continue |
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df_text.reset_index(inplace=True, drop=True) |
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try: |
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if df_text["label"][0] != df_text["label"][1]: |
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df_text = df_text[:2] |
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elif df_text["label"][0] != df_text["label"][2] and len(df_text) > 2: |
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df_text = df_text.iloc[[0, 2], :] |
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df_text.reset_index(inplace=True, drop=True) |
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df_new = df_text[:1] |
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df_new["switch"] = df_new["switch"].apply( |
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lambda x: [df_text["switch"][0], df_text["switch"][1]] |
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) |
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lang.append("zh") |
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original.append("original") |
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o_text.append("?") |
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sent.append(df_new.iloc[0]["text"]) |
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toks.append(df_new.iloc[0]["toks"]) |
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pronoun.append(df_new.iloc[0]["pronoun"]) |
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switch.append(df_new.iloc[0]["switch"]) |
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except: |
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continue |
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total_df = pd.DataFrame( |
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{0: lang, 1: original, 2: o_text, 3: sent, 4: toks, 5: pronoun, 6: switch} |
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) |
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count = total_df[5].apply(lambda x: len(x[0])) |
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total_df[4] = total_df[4].apply(lambda x: json.dumps(x)) |
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total_df[5] = total_df[5].apply(lambda x: json.dumps(x)) |
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total_df[6] = total_df[6].apply(lambda x: json.dumps(x)) |
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return total_df, count |
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def remove_at(i, s): |
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return s[:i] + s[i + 1 :] |
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def remove_to(x): |
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if x["count"] == 2: |
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return remove_at(x["sentence"].index("_") + 1, x["sentence"]) |
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else: |
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return x["sentence"] |
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def get_original_splits(): |
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for j, i in enumerate(["en", "jp", "ru", "pt", "fr", "zh"]): |
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if j == 0: |
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dfx = datasets.load_dataset("xwinograd", i)["test"].to_pandas() |
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dfx["lang"] = i |
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else: |
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df = datasets.load_dataset("xwinograd", i)["test"].to_pandas() |
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df["lang"] = i |
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dfx = pd.concat([dfx, df]) |
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return dfx |
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def get_examples_from_clue(): |
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dataset = load_dataset("clue", "cluewsc2020") |
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df = dataset["train"].to_pandas() |
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df_val = dataset["validation"].to_pandas() |
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df = pd.concat([df, df_val]) |
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new_examples, count = convert_to_format(df) |
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new_examples.reset_index(inplace=True, drop=True) |
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new_examples.to_csv( |
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"xwinograd/data/xwinograd.tsv", sep="\t", header=None, index=False |
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) |
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df_post = datasets.load_dataset("xwinograd", "zh") |
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df_post = df_post["test"].to_pandas() |
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df_post["count"] = count |
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df_post["sentence"] = df_post.apply(remove_to, axis=1) |
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df_post = df_post[["sentence", "option1", "option2", "answer"]] |
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return df_post |
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if __name__ == "__main__": |
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dfx = get_original_splits() |
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df_post = get_examples_from_clue() |
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df_post.to_json("new_examples_updated.json", orient="split") |
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df_post["lang"] = "zh" |
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dfx = pd.concat([dfx, df_post]) |
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dfx.drop_duplicates() |
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dfx.reset_index(inplace=True, drop=True) |
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dfx.to_json("all_examples_updated.json", orient="split") |
