Since Entity Resolution involves dealing with different variations of the same entity, there are multiple ways in which the entity can be represented. Here are some representative samples of fuzzy matching using Reifier. With machine learning for entity matching, it is much easier to handle the different patterns. Imagine writing rules for each of these cases, across multiple fields! For Reifier, training samples to cover each of these cases is not needed, the whole point behind AI is that it should be able to generalize well to unseen cases.
Multiple Fields Of Different Types
Typographical errors and misspellings
Out of order words
Leading and trailing spaces
Titles, suffixes and prefixes