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from pathlib import Path |
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from typing import Annotated |
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import typer |
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from .alignment import ( |
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find_closest_text, |
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to_aligned_character_indices_series, |
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to_character_indices_series, |
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) |
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from .data import read_aste_file, read_sem_eval_file |
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from .sentiment import to_nice_sentiment |
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app = typer.Typer() |
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@app.command() |
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def aste( |
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aste_file: Annotated[Path, typer.Option()], |
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output_file: Annotated[Path, typer.Option()], |
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) -> None: |
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df = read_aste_file(aste_file) |
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df = df.explode("triples") |
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df = df.reset_index(drop=False) |
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df = df.merge( |
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df.apply(to_character_indices_series, axis="columns"), |
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left_index=True, |
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right_index=True, |
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) |
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df["sentiment"] = df.triples.apply(lambda triple: to_nice_sentiment(triple[2])) |
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df = df.drop(columns=["triples"]) |
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print(df.sample(3)) |
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output_file.parent.mkdir(exist_ok=True, parents=True) |
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df.to_parquet(output_file, compression="gzip") |
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@app.command() |
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def sem_eval( |
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aste_file: Annotated[Path, typer.Option()], |
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sem_eval_file: Annotated[Path, typer.Option()], |
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output_file: Annotated[Path, typer.Option()], |
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) -> None: |
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df = read_aste_file(aste_file) |
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sem_eval_df = read_sem_eval_file(sem_eval_file) |
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df["original"] = df.text |
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df["text"] = find_closest_text(original=df.original, replacement=sem_eval_df.text) |
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df = df.explode("triples") |
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df = df.reset_index(drop=False) |
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df = df.merge( |
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df.apply(to_aligned_character_indices_series, axis="columns"), |
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left_index=True, |
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right_index=True, |
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) |
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df["sentiment"] = df.triples.apply(lambda triple: to_nice_sentiment(triple[2])) |
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df = df.drop(columns=["original", "triples"]) |
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print(df.sample(3)) |
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output_file.parent.mkdir(exist_ok=True, parents=True) |
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df.to_parquet(output_file, compression="gzip") |
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if __name__ == "__main__": |
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app() |
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