Natural Language Processing
We comprehend and annotate natural language processing (NLP) data. We also offer the best NLP annotation tools for your computers, applications, and machine learning models to easily comprehend human languages and gain insight from text and audio data.
Natural Language Processing Annotation Services
Unstructured text-based data can yield interesting insights if processed properly. NLP comes in handy at this point. The AI text annotation & labeling subject matter experts provide best NLP annotation & labeling solutions by using top NLP annotation tools. We utilize the most efficient NLP platforms to make text & speech data comprehensible to computers and machine learning models.
Types of NLP Text Annotation Services
NLP text annotation involves adding metadata to a text to improve the performance of NLP models.
NLP data annotators assign a sentiment label (positive, negative, or neutral) to text to train a model to automatically classify the sentiment of a text. It is useful in applications like social media monitoring and customer sentiment analysis.
Named Entity Recognition
NLP data annotators mark up entities in text (person names, locations, and organizations) to train a model to automatically identify and classify them. It is handy in applications like information extraction and document classification.
Part-of-Speech (POS) Tagging
NLP data annotators tag each word in a sentence with its corresponding part of speech (noun, verb, adjective, etc.). This is used to improve tasks such as parsing and information extraction.
NLP data annotators classify documents into pre-defined categories (spam vs. non-spam, news articles by topic, or customer support requests) by type. This is used to route incoming customer requests to the appropriate department.
NLP data annotators provide translations of a source text to train a model to translate text from one language to another. This is used for global businesses that need to translate content for international customers.
NLP data annotators transcribe spoken words into text to train a model to automatically recognize and transcribe speech. This is used in applications like voice-activated assistants and speech-to-text transcription.
NLP Use Cases
NLP applications are used across many industries. From powering search and recommendation engines, processing automation till social media content and customer feedback.
Use NLP annotation for analysing medical records, clinical notes, and patient data to offer better patient care and treatment.
Use NLP annotation for analysing social media data, customer reviews, and surveys to gain an in-depth insight of customer preferences, sentiments, and behavior.
Use NLP annotation for offering a robust solution for sensitive data which needs to be processed for the public sector at the federal, local, and state level.
Use NLP annotation for analysing financial reports, news articles, and social media data in order to predict market trends, understanding customers, and identifying potential investment options.
Use NLP annotation to study customer reviews, search queries, and product descriptions for optimizing search results, improving product recommendations, and understanding consumer needs in a better way.
Use NLP annotation for analysing student feedback, course evaluations, and learning materials for improving learning resources and understanding student needs in a better manner.
Key Capabilities of Our NLP Team
We offer NLP data annotation services for AI NLP projects that comply with international quality standards.
Data Collection & Curation
We can collect and curate large amounts of data from various sources like text corpora, social media, and online reviews.
We offer data annotation experts who understand various NLP tasks like named entity recognition, sentiment analysis, etc. for training ML models.
We have developed processes for verifying the accuracy of annotations, identifying, and correcting errors in data.
Our NLP training data experts have domain expertise for providing quality services.
Collaboration & Communication
Our NLP experts can effectively communicate and collaborate their findings with other members of their team.
Our NLP experts are proficient in programming languages and working with machine learning libraries like scikit-learn and TensorFlow.
Our NLP experts are up-to-date with the latest developments in NLP research and technology.
NLP Annotation Tools & Techniques
We make texts comprehendible to AI-driven machines by adding the right metadata in each sentence of your texts.
We classify and assign tags to natural language texts so that they become understandable to machines.
We work in tandem with language experts and advanced speech recognition technology to deliver the best turnaround times and accuracy for speech-to-text conversion.
We add captions and subtitles to your videos to make them more accessible, searchable, and engaging for your viewers.
We add proper metadata and tags in audio recordings to enable machines to interpret sounds and voices.
This is the process of extracting relationships between two entities in unstructured sources such as raw text in a sentence.
Named Entity Recognition
We extract relevant information from the text document to enable machines to understand the key text in NLP entity extraction for deep learning.
We utilize conversational samples from client chat logs, email archives, and website content to create high-quality and customized chatbot training data.
We help you develop intelligent sentiment analysis algorithms by providing an accurate sentiment analysis dataset through our trained professionals.
We provide you with high-quality feature classification dataset for training your NLP model to determine which words should be translated into which language based on its sentiment.
We offer high-quality intent classification dataset to make conversations more interactive and supportive for potential customers.