Enhancing the NLP model's understanding with accurately labeled textual data
850+
Full time
employees
25+ Years in
business
99.95% Data
accuracy
3850+ Happy
clients
ISO 9001:2015
27001:2022
850+
Full time
employees
25+ Years in
business
99.95% Data
accuracy
3850+ Happy
clients
ISO 9001:2015
27001:2022
Accurately capturing linguistic nuances, context-dependent meanings, and domain-specific terminology in text annotations is crucial for enhancing NLP model performance. However, maintaining annotation quality at scale without sacrificing contextual relevance remains a significant challenge. At Data-Entry-India.com, we tackle these roadblocks with human-supervised text annotation services. Leveraging decades of experience, domain expertise, and multi-tier quality control processes, we create training datasets for text-based NLP models to perform tasks like sentiment analysis, entity recognition, language translation, and intent classification.
By prioritizing data security and compliance (HIPAA, GDPR, etc.), we safeguard sensitive information throughout the labeling process, building a foundation of trust.
By combining human expertise with AI-driven automation, we create training datasets that significantly improve the performance of NLP models for real-world applications. Our text annotation services comprise:
Different parts of a text are labeled (based on its context, intent, subject, and structure) by annotators through the application of custom or pre-defined classification schemas. The annotated textual data enhances the language & contextual understanding of NLP models for automated content management, text analysis, question-answering/conversational AI, text summarization, and word sense disambiguation.
We segment text into contextually relevant phrases and annotate them according to grammatical context (noun phrases, verb phrases, and modifiers) for lexical analysis. By providing context-aware, structured training data, we enable NLP models to accurately capture dialectal variations, idiomatic expressions, and language patterns for enhanced usability across various applications.
Our experts assign unique identities to individual entities (such as names, dates, and locations) and use relationship extraction techniques to establish connections between each part of a sentence. This contextually rich metadata improves the performance of AI systems, like chatbots or document search tools, by making it easier for them to understand and retrieve the right information quickly.
Upon understanding the semantic context of the text, the annotators assign labels such as positive, negative, or neutral to each sentence or phrase. This enriched text data trains AI models (used in chatbots and consumer service systems) to analyze and interpret users' sentiments more effectively and deliver emotionally-aware interactions for better engagement.
By assigning descriptive tags and additional information (related to keywords associated with the document, file type, file name, author details, etc.), we provide more context to textual data. Such detailed text annotation enables AI systems to understand and locate information more efficiently for the seamless organization of digital assets and enhanced search engine discoverability.
For high-end NLP applications such as speech recognition, syntactic parsing, and language translation, we perform text corpus labeling. Each phrase is tagged with its part of speech (noun, verb, adjective) using pre-defined rules and contextual cues. This labeled text data helps AI models build syntax trees and understand sentence structure better.
Our text annotation company excels in creating industry-specific training datasets for specialized applications such as medical diagnosis systems, IoT predictive maintenance apps, and trading fraud detection tools. By handling complex annotation tasks for text data, we ensure NLP models perform effectively in even the most demanding scenarios.
By annotating product data, reviews, and customer interactions, we train AI systems for sentiment analysis and personalized product recommendations.
Through the detailed labeling of medical journals, electronic health records, and patient notes, our healthcare text annotation services facilitate advanced diagnostics, drug discovery, and personalized treatment plans for improved patient care.
Text annotation of transactional data, customer complaints, and legal documents allows financial institutions to identify anomalies, potential fraudulent activities, and investment-related risks utilizing fraud detection systems.
Through semantic annotation and POS tagging techniques, we label customer inquiries and support tickets to enable chatbots to understand users' intent and improve response accuracy.
By tagging positive, negative, and neutral comments on social media ad campaigns and posts, we enable marketing agencies to measure the success of their outreach campaigns and optimize advertising strategies for improved outcomes.
By tagging relevant legal terms, case precedents, and clauses, we enable AI-powered document summarization systems to quickly extract relevant key points and prepare case summaries for further research.
We analyze your text data labeling needs, project goals, and the complexities of defining guidelines. We can also share labeled sample data to help you assess service quality.
We prepare the provided dataset for annotation by removing inconsistencies, formatting issues, and duplicates.
Through manual and automated text annotation techniques, we create high-quality training datasets for NLP models, adhering to data labeling guidelines.
Our subject matter experts validate the annotated text data for accuracy and contextual relevance through multi-level quality checks.
Annotated data is securely delivered to the client in the specified format, and required changes are made based on their feedback.
Our expert annotators for NLP projects are adept at utilizing prominent text data annotation tools. We can also adapt to your proprietary software for customized labeling requirements.
Leading the way in text annotation outsourcing services, we combine decades of experience with prominently used AI tools to deliver unparalleled accuracy and data security. Whether it's for training AI models or enhancing automation, our human-in-the-loop text labeling approach helps businesses scale their AI capabilities.
Our trust builders include:
By opting for high-quality text annotation outsourcing services, you can save internal resources from investing their time in complex jobs of metadata tagging, text annotation, and so much more. Our expert annotators for NLP projects ensure you get training-ready datasets within the stipulated time frame and budget, adhering to HIPAA and GDPR compliance. Request a free quote/sample by sharing your project details with us at info@data-entry-india.com
Get your free sample
+1 585 283 0055
+44 203 514 2601
+919311468458
