Datasets:
from __future__ import annotations | |
import re | |
from dataclasses import dataclass | |
from typing import Literal | |
AspectWordIndices = tuple[int, ...] | |
OpinionWordIndices = tuple[int, ...] | |
Sentiment = Literal["NEG", "NEU", "POS"] | |
Triplet = tuple[AspectWordIndices, OpinionWordIndices, Sentiment] | |
word_pattern = re.compile(r"\S+") | |
class WordSpan: | |
start_index: int | |
end_index: int # this is the letter after the end | |
class WordSpans: | |
spans: list[WordSpan] | |
def make(text: str) -> WordSpans: | |
spans = [ | |
WordSpan(start_index=match.start(), end_index=match.end()) | |
for match in word_pattern.finditer(text) | |
] | |
return WordSpans(spans) | |
def to_indices(self, span: tuple[int, ...]) -> tuple[int, int]: | |
word_start = span[0] | |
word_start_span = self.spans[word_start] | |
word_end = span[-1] | |
word_end_span = self.spans[word_end] | |
return word_start_span.start_index, word_end_span.end_index - 1 | |
class CharacterIndices: | |
aspect_start_index: int | |
aspect_end_index: int | |
aspect_term: str | |
opinion_start_index: int | |
opinion_end_index: int | |
opinion_term: str | |