如何借助另一列数据与POS标签替换句子中的指定字符串？

Got it, let's work through this problem step by step. You want to swap out any case-variant of the string in col1 from the sentence in col2, replacing it with the POS tag that matches the col1 value. Here's a complete solution that builds on the NLTK setup you already tried:

1. Import Required Libraries #

First, make sure you have these imports (I added pandas since we're working with a DataFrame):

import pandas as pd
import re
from nltk import word_tokenize, pos_tag

2. Generate POS Tags for Col1 Values #

First, we need to get the correct POS tag for each entry in col1. We'll tag each value individually and store it in a new column for easy access:

# Assuming your DataFrame is named `df`
df['pos_tag'] = df['col1'].apply(lambda x: pos_tag(word_tokenize(x))[0][1])

This takes each string in col1, tokenizes it (though these are single tokens), runs POS tagging, and pulls the tag itself (the second item in the resulting tuple).

3. Create the Replacement Function #

Next, we'll make a function that scans a sentence from col2 and replaces any case-insensitive match of the col1 string with its POS tag. Using regex ensures we catch variations like MTMB2, MmM2, or bbb2 regardless of capitalization:

def replace_target_with_tag(row):
    # Escape special characters in the target string to avoid regex issues
    target_pattern = re.compile(re.escape(row['col1']), re.IGNORECASE)
    # Replace all matches in the col2 sentence with the corresponding POS tag
    return target_pattern.sub(row['pos_tag'], row['col2'])

4. Apply the Function to Your DataFrame #

Finally, apply this function across each row to generate the output column:

df['output'] = df.apply(replace_target_with_tag, axis=1)

Testing with Your Example Data #

If you run this with your sample input:

You'll get exactly the output you're looking for.

The key difference from your initial attempt is that we're focusing on tagging the specific col1 values first, then targeting those exact strings (case-insensitively) in col2 for replacement, rather than tagging the entire col2 sentence.

内容的提问来源于stack exchange，提问作者balarin