AI engineering glossary · NLP embeddings
What is STS (semantic textual similarity)?
Semantic textual similarity (also called STS): A benchmark task in which systems score how similar in meaning two sentences are, and are compared with human ratings, typically using correlation. It is a standard way to evaluate sentence embeddings.
Semantic textual similarity: an example
A model gives 0.87 to a sentence pair humans rated 4.5 out of 5, and its scores are correlated with the human ratings across the dataset.
Related terms
More NLP embeddings terms
- Sentence embedding
- Sentence segmentation
- Sentence-BERT
- SentencePiece
- Sentiment analysis
- Sequence labelling
- Siamese network
- Skip-gram
Where you learn it
Semantic textual similarity is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.