Smart wordlists that understand semantic meaning, similar words, and obfuscations
YouTube
to a wordlist, the model understands that Vimeo
is similar and it can be flagged as well without you having to add Vimeo
to the wordlist. It also means that the wordlist understands tense and plural forms without you having to add them.
This is what makes our wordlists smarter than a simple match on a list of words.
apple
twice, it will automatically be deduplicated.
Adding phrases
You can add phrases as well as single words. Phrases are matched exactly as you type them, but also work with semantic meaning. For example, if you add the phrase New York
to the wordlist, it will also match NYC
.
Embedding processing
If you add a lot of words at once, the wordlist will automatically process them in the background to understand semantic meaning. This can take a few minutes for large wordlists, and the wordlist will not detect words until this processing is complete.
wordlists
field when you use the moderate/text endpoint. You can identify the wordlist by the id
field or the name
.
Field | Description |
---|---|
id | The unique identifier of the wordlist |
name | The name of the wordlist |
found | Indicates if the wordlist found a match |
flagged | Indicates if the wordlist caused the content to be flagged. Can differ from found if the wordlist is set to allow list or pass through mode |
matches | Contains the words that were matched |
score | Indicates the similarity score between the word in the text and the word in the wordlist |