Abstractive Summarisation

Sentiment Analysis

The computational study of people's opinions, emotions, and attitudes expressed in text.

Text Classification

The task of assigning predefined categories or labels to text documents based on their content.

Text Summarisation

The process of creating a concise and coherent summary of a longer text document while preserving key information.

Topic Modelling

An unsupervised technique for discovering abstract topics that occur in a collection of documents.

Aspect-Based Sentiment Analysis

A fine-grained sentiment analysis approach that identifies opinions directed at specific aspects or features of an entity, such as a product's price, quality, or design.

A subword tokenisation algorithm that iteratively merges the most frequent character pairs to build a vocabulary.

Bidirectional Encoder Representations from Transformers — a language model that understands context by reading text in both directions.

The process of producing coherent and contextually relevant text using AI language models.

Identifying semantic relationships between entities mentioned in text.

The classification of user utterances into predefined categories representing the user's goal or purpose, a fundamental component of conversational AI and chatbot systems.

The automated production of source code from natural language specifications or partial code context, powered by large language models trained on programming repositories.

The generation of machine-readable formatted responses such as JSON, XML, or code from language models, enabling reliable integration with downstream software systems.

Techniques for identifying when AI language models generate plausible but factually incorrect or unsupported content.