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Text & NLP Annotation

Linguistically precise annotation for natural language processing. Named entity recognition, sentiment analysis, classification, and relation extraction — in 40+ languages.

Text and NLP annotation services

Training Data for Language Understanding

Language models are only as good as the text data they train on. Our NLP annotation services provide the structured, human-labeled text datasets that power chatbots, search engines, content moderation systems, and document processing pipelines. Our linguists and domain specialists annotate text with the nuance machines need — disambiguating entities, capturing sentiment gradients, and mapping complex relationships between concepts. We support over 40 languages including Arabic, Urdu, Hindi, Mandarin, and all major European languages.

  • Named entity recognition (NER) with custom taxonomies
  • Sentiment and emotion analysis at document and aspect level
  • Text classification and intent detection
  • Relation extraction and knowledge graph construction
  • 40+ languages with native-speaker annotators
Capabilities

NLP Annotation Methods

Specialized text labeling techniques for every natural language processing challenge.

Named Entity Recognition

Span-level annotation of persons, organizations, locations, dates, monetary values, medical terms, and custom entity types. We build and maintain complex nested entity taxonomies for specialized domains like legal, healthcare, and finance.

Sentiment & Emotion Analysis

Document-level and aspect-level sentiment scoring on fine-grained scales. Our annotators capture sentiment polarity, intensity, sarcasm, and emotion categories (joy, anger, fear, surprise) with contextual awareness across domains.

Text Classification

Multi-label and hierarchical classification for topics, intent, urgency, toxicity, and custom categories. We handle taxonomies with hundreds of classes and provide inter-annotator agreement metrics for every label.

Relation Extraction

Annotating semantic relationships between entities — "works at," "causes," "treats," "located in" — to build structured knowledge graphs from unstructured text. Critical for biomedical NLP, legal AI, and enterprise search.

Intent & Slot Filling

Utterance-level intent classification and slot extraction for conversational AI. We label user queries with intents and extract key parameters (dates, locations, product names) for chatbot and virtual assistant training.

Coreference Resolution

Linking pronouns and mentions to their referent entities across documents. Essential for building models that understand discourse structure, summarize long documents, and resolve ambiguous references in conversation.

FAQ

Frequently Asked Questions

We support 40+ languages with native-speaker annotators. Our strongest coverage includes English, Arabic, Urdu, Hindi, Spanish, French, German, Mandarin, Japanese, Korean, Portuguese, Turkish, and all major European languages. For specialized or low-resource languages, we recruit and train annotators from our global network.
We establish detailed annotation guidelines with your team before production begins, including edge case examples. During annotation, ambiguous cases are flagged for adjudication by senior annotators or domain experts. We measure inter-annotator agreement (IAA) continuously and refine guidelines iteratively to reduce ambiguity over time.
Yes. We maintain specialized annotator pools for healthcare (clinical notes, radiology reports), legal (contracts, case law), financial (earnings calls, SEC filings), and technical (code documentation, patents) domains. These annotators receive domain-specific training and pass qualification tests before joining your project.
We deliver annotations in standard NLP formats including CoNLL, IOB/IOB2, spaCy JSON, Prodigy JSONL, and custom formats. For relation extraction, we provide structured triples. All annotations include confidence scores and annotator metadata for full traceability.
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Build Better Language Models With Expert Annotation

Send us a sample corpus and we'll return annotated results demonstrating our linguistic precision, consistency, and multilingual capabilities.

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