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Meaning is influenced by a variety of factors
Why natural language processing needs human-labeled data
Interpreting natural language is complex and nuanced, even for humans. Meaning is influenced by context, frames of reference, individual preferences, and situational constraints, among other variables. While modern machine learning models have learned to predict and generate text, they are not yet able to execute sophisticated tasks like sentiment analysis or intent recognition without large volumes of human-labeled data that capture semantic properties.
Natural Language Processing Capabilities
Our platform and purpose-built tools support annotation for Named Entity Recognition, part-of-speech tagging, text classification, and speech recognition, enabling customers to extract meaning out of raw audio or text. NLP tasks are deployed to a team of human annotators who are trained to handle use cases involving a high degree of subjectivity like intent recognition and sentiment analysis.
Chatbots
Categorize complex queries into fixed classes to design interactions
Customer Service
Use pattern recognition to Identify customer objectives
Sentiment Analysis
Overlay human decisions to extract context and information
Virtual Assistants
Train virtual assistants to deliver personalized interactions
Mobile Apps
Keep NLP-driven features up-to-date with continuous model validation
Text Classification
Nominate inappropriate content for human judgment and reviews
Information Extraction
Extract structured information from unstructured data
Intent Recognition
Create associational relationships to identify intent
Semantic Enrichment
Infer meaning and improve content utility through text augmentation
Platform & Tools
The platform is the core of our high-performance data labeling. Annotation tools, workflow configuration, job distribution, worker evaluation, and quality control are all managed within our platform with varying degrees of ML assistance.
Known Workforce
Alegion qualifies and trains a team of human annotators who are identified as a match for your project. Our teams can be NDA-ready, geo-isolated, or selected according to specific compliance requirements. Or, you can bring your own team.
ML Project Expertise
We don’t just onboard you onto our platform and hope for the best. You’ll be assigned an Alegion solutions specialist who understands your problem space and continually iterates on your labeling tasks to deliver on your accuracy requirements.
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CCO
Alegion's annotation tools, machine learning assistance, and quality control strategies have greatly improved confidence in our AI initiatives.