- Classification Tasks
- Text Classification : Categorizing text into predefined classes or categories.
- Sentiment Analysis : Determining the sentiment or emotion expressed in a piece of text.
- Reading Comprehension : Understanding and answering questions based on a given text.
- Analyze and Evaluate : Assessing and evaluating text based on specific criteria.
- Topic Modeling : Identifying topics or themes within a collection of documents.
- Intent Recognition : Determining the user's intention or goal behind a given text.
- Generation Tasks
- Text Generation : Creating new text based on certain conditions or prompts.
- Ideas and Brainstorming : Generating creative writing prompts, ideas, and brainstorming sessions.
- Copywriting and Marketing : Creating persuasive and engaging content for marketing and advertising purposes.
- Question Generation : Crafting relevant and meaningful questions based on a given text.
- Transformation Tasks
- Paraphrasing : Rewriting text to convey the same meaning using different words.
- Translation : Converting text from one language to another.
- Proofreading and Editing : Correcting and improving text for grammar, style, and clarity.
- Stylometry : Modifying text to match a specific writing style or author's voice.
- Simplification : Rewriting complex text to make it more understandable for a wider audience.
- Language Style Transfer : Adapting the style of a text to match a specific tone, formality level, or dialect.
- Comparison Tasks
- Comparison : Comparing two or more pieces of text based on specific attributes.
- Compare and Contrast : Identifying similarities and differences between two or more texts.
- Near-Duplicate Detection: Identifying nearly identical instances of text, useful for detecting content redundancy or repurposing.
- Textual Similarity: Measuring the degree of semantic similarity or equivalence between two pieces of text.
- Extraction Tasks
- Information Extraction : Extracting specific information or data from unstructured text.
- Named Entity Recognition : Identifying and classifying named entities (e.g., person names, locations, organizations) in text.
- Keyword Extraction : Identifying and extracting significant words or phrases from a given text.
- Relation Extraction : Discovering and categorizing relationships between entities within a text.
- Summarization Tasks
- Text Summarization : Creating a concise summary of a longer piece of text.
- Extractive Summarization : Generating a summary by selecting important sentences or phrases from the original text.
- Abstractive Summarization : Producing a summary that captures the main points of the original text, but may use new wording or phrasing.
- Synthesis Tasks
- Synthesis and Merging : Combining information from multiple sources to create a coherent and comprehensive output.
- Programming Tasks
- Natural Language Programming : Using natural language to interact with or instruct computer programs.
- Code Generation : Automatically generating code based on natural language descriptions or specifications.
- Natural Language Interface : Allowing users to interact with software applications through natural language commands or queries.
- Automated Debugging : Identifying and fixing programming errors based on natural language descriptions of the problem.
- Inference Tasks
- Implicit Information Extraction: Inferring information that is not explicitly stated in the text.
- Commonsense Reasoning: Making inferences about everyday situations and events.
- Natural Language Inference: Determining whether a statement is true, false, or indeterminable based on a given context.
- Textual Entailment: Determining whether a given text implies a hypothesis or statement.