Compare 2 DataFrames for semi matching rows

I have 2 dataframes with strings in the cells:

df1

ID  t1  t2  t3
0   x1  y1  z1
1   x2  y2  z2 
2   x3  y3  z3 
3   x4  y4  z4  
4   x1  y5  z5 

df2

ID  t1  t2  t3
0   x3  y3  z3
1   x4  y4  z4 
2   x1  y1  z1 
3   x2  y2  z2  
4   x1  y7  z5 

I found that I can compare the differences in rows with:

#exactly the same t1, t2, and t3
pd.merge(df1, df2, on=['t1', 't2', 't3'], how='inner')

This will find an exact match between the rows (where t1 in df1 equals t1 in df2, etc.).

How can I find a semi match between the 2 dataframes for a specific column? That is, where there could be a difference in only the specified column in addition to the exact matches? For example, if I specify t2, a match will be t1 in df1 = t1 in df2, t2 in df1 != df2, t3 in df1 = t3 in df3 (for example, row ID=4 in the 2 dataframes will match this in addition to the exact matches).

from Compare 2 DataFrames for semi matching rows