Diraflow
Diraflow
Power your AI with high-quality NLP annotation — text classification, named entity recognition, sentiment analysis, intent detection, and dialogue annotation from linguistics specialists.
Nine specialized annotation types covering every NLP AI use case — from text classification to conversational AI and content moderation.
Text classification assigns topic, intent, priority, and domain labels to documents, emails, support tickets, and web content. Annotators categorize text with high accuracy, capturing thematic intent and business relevance. Essential for routing systems, content management, and applications requiring automatic text organization and relevance scoring.
Common use cases: Email spam filtering and routing, support ticket prioritization, content moderation and categorization, document classification, news topic tagging, sentiment-based routing, and business process automation.
Named entity recognition identifies and labels entities in text — people, locations, organizations, dates, products, medical terms, and financial instruments. Annotators mark entity boundaries and types with precision, handling ambiguous references and cross-domain contexts. Critical for information extraction, knowledge graph construction, and applications requiring detailed entity understanding.
Common use cases: Resume and job description parsing, biomedical entity extraction, financial document analysis, knowledge graph building, person and organization identification, product mention detection, and domain-specific information extraction.
Sentiment annotation captures polarity — positive, negative, neutral — and emotion tagging detects fine-grained emotional states from text. Annotators assess customer sentiment in reviews, social media, and feedback with nuance, capturing sarcasm, mixed sentiments, and domain-specific context. Essential for brand monitoring, customer satisfaction analysis, and applications requiring emotional intelligence.
Common use cases: Customer review sentiment scoring, social media brand monitoring, customer feedback analysis, product reputation management, employee sentiment tracking, market research analysis, and emotion-aware personalization systems.
Dialogue annotation captures multi-turn conversations with context tracking, speaker roles, intent sequences, and response quality evaluation. Annotators analyze conversational dynamics, coreference resolution, and discourse structure. Essential for conversational AI, dialogue system training, and applications requiring nuanced understanding of multi-party interactions.
Common use cases: Chatbot and dialogue system training, conversational AI evaluation, customer service interaction analysis, meeting transcription quality control, dialogue coherence assessment, and empathy-aware conversational agent development.
Content moderation identifies harmful, offensive, or policy-violating language — hate speech, harassment, misinformation, explicit content. Annotators apply nuanced judgment, understanding context, culture, and intent. Essential for safe online platforms, spam detection, and applications requiring content quality and safety assurance.
Common use cases: Social media content filtering, toxicity and hate speech detection, harassment prevention, misinformation flagging, brand safety for advertising, platform policy enforcement, and online community safety systems.
Speech-to-text transcription converts audio to text with timestamps and speaker diarization support. Keyphrase and summary tagging highlights critical information from documents and transcripts. Annotators extract keyphrases, summaries, and highlights that capture essential meaning. Essential for searchable knowledge systems, meeting notes, and applications requiring information extraction and summarization.
Common use cases: Meeting and conference transcription, podcast transcription with speaker labels, interview documentation, document summarization for search, keyphrase extraction for tagging, research paper analysis, and information retrieval systems.
We employ linguists, content specialists, and NLP domain experts who understand semantic nuance, cultural context, and business requirements. Rigorous quality checks ensure annotations meet production standards and capture the linguistic depth required for advanced language models.
Send us details about your NLP annotation needs and we'll provide a tailored proposal — scope, timeline, and pricing — within one business day.
Include annotation type, text samples, and timeline.