AI and ML Network Services
Text and NLP Annotation Services
Professional text annotation and NLP data labeling services for language models. Named entity recognition, text classification, sentiment analysis, and custom NLP labeling with expert annotators.
AI and ML Network provides professional text annotation and NLP data labeling services for teams building language models, chatbots, search engines, and NLP applications.
Text Annotation Types
Named Entity Recognition (NER)
Precise entity boundary marking and classification — identifying people, organizations, locations, dates, monetary values, and custom entity types in unstructured text.
Text Classification
Document-level and sentence-level classification for topic categorization, intent detection, spam filtering, content moderation, and custom taxonomy assignment.
Sentiment Analysis
Sentence-level and aspect-level sentiment labeling (positive, negative, neutral) with configurable granularity. Used for product review analysis, social media monitoring, and brand perception tracking.
Relation Extraction
Identifying and labeling relationships between entities in text — used for knowledge graph construction, biomedical text mining, and information extraction pipelines.
Intent Classification
Labeling user queries and messages with intent categories for chatbot training, voice assistant development, and conversational AI systems.
Our NLP Annotation Process
- Schema design — We review your entity types, classification taxonomy, or labeling schema
- Guideline creation — We build annotation guidelines with edge case examples
- Calibration round — Small batch to verify annotator understanding and inter-annotator agreement
- Full annotation — Expert annotators label your text data following strict guidelines
- QA and delivery — Quality validation, consistency checks, and export in your required format
If you need text annotation for your NLP project, go to the Start Project page and send your requirements.
Frequently Asked Questions
What types of text annotation do you provide? +
We provide named entity recognition (NER) annotation, text classification, sentiment analysis labeling, intent classification, relation extraction, POS tagging, text summarization evaluation, and custom NLP annotation schemas for large language models and NLP pipelines.
Which tools do you use for text annotation? +
We primarily use Label Studio for text annotation due to its flexible template system that handles NER, classification, relation extraction, and multi-label tasks. We also support Prodigy, Doccano, and custom annotation interfaces depending on project requirements.
Can you handle multi-language text annotation? +
Yes, we handle text annotation in multiple languages. For languages requiring native-level fluency for accurate semantic understanding, we work with language-specialist annotators. For structural annotation tasks like entity boundary marking, our standard team handles multilingual content.
Ready to Start?
Get a free sample batch to test our quality before committing.