Get the sem-eval converter working

src/alignment.py

@@ -14,10 +14,11 @@ def find_closest_text(
 ) -> pd.Series:
     # Returns a series of the replacement values aligned to the original values
     no_space_replacements = {text.replace(" ", ""): text for text in replacement}
-    result = original.str.replace(" ", "").map(no_space_replacements)
+    original_text = original.str.replace(" ", "")
+    result = original_text.map(no_space_replacements)
     non_perfect_matches = result.isna().sum()
 
-    assert non_perfect_matches / len(original) <= 0.05, (
+    assert non_perfect_matches / len(original) <= 0.10, (
         "Poor alignment with replacement text. "
         f"{non_perfect_matches:,} of {len(original),} rows did not match well"
     )
@@ -28,7 +29,8 @@ def find_closest_text(
         )
         return replacement.iloc[distances.argmin()]
 
-    result.loc[result.isna()] = result[result.isna()].apply(closest)
+    result.loc[result.isna()] = original_text[result.isna()].apply(closest)
+    result = result.str.strip()
     return result
 
 
@@ -63,6 +65,16 @@ def to_character_indices(
     )
 
 
+def to_aligned_character_indices_series(row: pd.Series) -> pd.Series:
+    indices = to_character_indices(triplet=row.triples, text=row.original)
+    result = to_aligned_character_indices(
+        original=row.original,
+        replacement=row.text,
+        original_indices=indices,
+    )
+    return pd.Series(asdict(result))
+
+
 def to_aligned_character_indices(
     *,
     original: str,
@@ -147,7 +159,7 @@ def _aligned_start_index(
 def _aligned_end_index(
     text: str, original_index: int, indices: list[Optional[int]]
 ) -> int:
-    closest_before = min(
+    closest_before = max(
         index for index in indices if index is not None and index <= original_index
     )
     index = indices.index(closest_before)

src/main.py

@@ -3,8 +3,12 @@ from typing import Annotated
 
 import typer
 
-from .alignment import to_character_indices_series
-from .data import read_aste_file
+from .alignment import (
+    find_closest_text,
+    to_aligned_character_indices_series,
+    to_character_indices_series,
+)
+from .data import read_aste_file, read_sem_eval_file
 from .sentiment import to_nice_sentiment
 
 app = typer.Typer()
@@ -37,7 +41,24 @@ def sem_eval(
     sem_eval_file: Annotated[Path, typer.Option()],
     output_file: Annotated[Path, typer.Option()],
 ) -> None:
-    pass
+    df = read_aste_file(aste_file)
+    sem_eval_df = read_sem_eval_file(sem_eval_file)
+
+    df["original"] = df.text
+    df["text"] = find_closest_text(original=df.original, replacement=sem_eval_df.text)
+    df = df.explode("triples")
+    df = df.reset_index(drop=False)
+    df = df.merge(
+        df.apply(to_aligned_character_indices_series, axis="columns"),
+        left_index=True,
+        right_index=True,
+    )
+    df["sentiment"] = df.triples.apply(lambda triple: to_nice_sentiment(triple[2]))
+    df = df.drop(columns=["original", "triples"])
+
+    print(df.sample(3))
+
+    df.to_parquet(output_file, compression="gzip")
 
 
 if __name__ == "__main__":