Glossary

Semantic analysis

What is Semantic analysis?

Semantic analysis examines the meaning of language – not just which words appear, but what is meant. This includes interpreting ambiguous words correctly in context (such as “bank” as a financial institution or a riverside), recognising relationships between concepts and classifying statements by content. It underpins applications such as analysing customer feedback, question answering or search systems that should also understand differently worded queries with the same meaning.

Topics

NLP
meaning
text analysis

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Related terms

Natural Language Understanding (NLU)

Natural language understanding is the part of language processing that captures the meaning of an utterance: what intent lies behind it, which people, places or dates are mentioned, and what is its tone? Together with natural language generation (NLG), NLU forms one of the two sides of NLP. One example is a customer service system that recognises “My parcel still hasn't arrived” as a delivery enquiry.

NLP
Intent detection
+1

Sentiment analysis

Sentiment analysis automatically determines the mood or attitude a text expresses – usually positive, neutral or negative, sometimes finer-grained emotions. Businesses use it to evaluate large numbers of product reviews, support emails, surveys or social media posts and quickly see where customers are satisfied and where problems lie. Irony, sarcasm and mixed statements such as “fast delivery, disappointing quality” remain difficult, so samples should be checked by people.

NLP
customer feedback
+1

Template

Named entity recognition (NER)

Named entity recognition (NER) is a natural language processing technique that finds names of people, companies and places, as well as dates or amounts, in text and assigns each to a category. It turns free text into structured data. Example: the sender’s company, contact person, delivery date and invoice amount are extracted automatically from an email and transferred to a CRM.

NLP
Information extraction
+1

Template

Ontology

In computer science, an ontology is a formal model of a subject area that clearly defines concepts, their properties and the relationships between them. This allows people and machines to interpret data consistently and draw conclusions from it. Ontologies underpin many knowledge graphs, semantic search systems and data integration projects. Example: a product ontology states that an “e-bike” is a “bicycle” and has a “battery”.

knowledge modelling
semantics
+1