What is data annotation in AI?

Data annotation is the process of labeling raw data — images, text, audio, video, or 3D point clouds — so that machine learning models can learn from it. Annotated datasets are the foundation of supervised AI training. Without high-quality annotated data, AI models cannot achieve reliable accuracy.

What types of data annotation services does Data Terminal offer?

Data Terminal offers image annotation (bounding boxes, semantic segmentation, polygon, keypoints), video annotation (object tracking, activity recognition), text annotation (NER, sentiment, intent classification), audio annotation (transcription, speaker diarization, emotion tagging), LiDAR/3D point cloud annotation, document annotation (OCR correction, invoice parsing, form extraction), and RLHF (reinforcement learning from human feedback) for large language models.

What is the difference between data labeling and data annotation?

Data labeling assigns a single tag or category to a data item (e.g., 'cat' or 'dog'). Data annotation is broader — it includes labeling but also adds contextual metadata such as bounding boxes, segmentation masks, timestamps, relationships, and attributes. All labeling is annotation, but not all annotation is mere labeling.

How do you ensure quality in data annotation?

Data Terminal uses a multi-pass quality assurance process: custom annotation guidelines per project, pilot batch review, inter-annotator agreement (IAA) scoring, two-tier human review, automated consistency checks, and client feedback loops. We maintain 99.5% accuracy across projects.

What annotation output formats do you support?

We support all major annotation formats including COCO JSON, Pascal VOC XML, YOLO TXT, CVAT XML, Labelbox JSON, custom JSON/JSONL, and CSV. We can also deliver in any client-specified format.

How long does a data annotation project take?

Standard projects are delivered within 48–72 hours for small batches (up to 5,000 items). Large-scale projects (100,000+ items) are scoped with a dedicated timeline. Rush delivery is available for urgent AI training requirements.

Can Data Terminal handle large-scale data annotation projects?

Yes. Data Terminal has handled projects exceeding 50 million annotations. We scale annotation teams on demand for high-volume requirements, with dedicated project managers and continuous quality monitoring.

Why choose India for data annotation services?

India offers a large pool of English-proficient, technically trained annotators at cost-effective rates — typically 60–70% lower than US or European providers — without compromising on accuracy. Indian annotation teams are experienced in medical, legal, automotive, and NLP domains.

What industries does Data Terminal serve with data annotation?

Data Terminal serves autonomous vehicles, healthcare AI (medical imaging), e-commerce, agriculture, robotics, content moderation, satellite/geospatial imaging, legal/finance NLP, retail, and conversational AI (chatbots, virtual assistants).

What annotation tools does Data Terminal use?

We work with CVAT, Labelbox, Scale AI-compatible pipelines, Roboflow, VGG Image Annotator (VIA), and custom in-house annotation tools. We can integrate with your existing annotation platform or provide a fully managed environment.

What is text annotation in NLP?

Text annotation is the process of labeling text data with structured metadata so natural language processing (NLP) models can learn from it. This includes marking named entities (people, organizations, locations), classifying sentiment, labeling intents, extracting relationships, and resolving coreferences. Data Terminal delivers 99.3% accuracy text annotation across 30+ languages for LLM training, chatbot development, and NLP research.

What types of text annotation does Data Terminal offer?

We offer Named Entity Recognition (NER), sentiment analysis, intent classification, relation extraction, coreference resolution, text summarization quality labels, semantic similarity scoring, linguistic annotation (POS tagging, dependency parsing), and multi-label text classification.

What is Named Entity Recognition (NER) annotation?

NER annotation identifies and labels named entities in text — people (PERSON), organizations (ORG), locations (LOC/GPE), dates (DATE), money (MONEY), and custom domain-specific entities. It is the most common text annotation task for information extraction, document understanding, and knowledge graph construction.

What is intent classification annotation?

Intent classification annotation labels user utterances with the underlying intent — for example, labeling 'book a flight to Mumbai' as BOOK_FLIGHT or 'what's the weather tomorrow' as CHECK_WEATHER. This data trains conversational AI and virtual assistant models to understand user goals.

How many languages do you support for text annotation?

Data Terminal supports 30+ languages including English, Hindi, Arabic, Spanish, French, German, Japanese, Chinese (Simplified/Traditional), Portuguese, Russian, Korean, Italian, Dutch, and major Indian languages (Telugu, Tamil, Kannada, Bengali, Marathi). Native-speaker annotators are used for all non-English tasks.

What is the difference between sentiment analysis and intent classification annotation?

Sentiment annotation labels the emotional tone of text (positive, negative, neutral, or fine-grained emotions like joy/anger/fear). Intent annotation labels what the speaker wants to accomplish (the goal behind the words). Both are used together for conversational AI — understanding both the mood and the request.

How do you ensure quality in text annotation?

We use Cohen's Kappa inter-annotator agreement (IAA) scoring — requiring >0.80 Kappa before scaling production. Every text annotation project gets a custom annotation schema, edge case guidelines, two-pass review, and a calibration batch before full scale. We consistently deliver 99.3% accuracy with IAA >0.85.

Why outsource text annotation to India?

India has the world's largest pool of English-proficient, technically trained text annotators — critical for NLP and LLM tasks. Data Terminal's Hyderabad-based team has domain expertise in legal, medical, financial, and e-commerce text annotation, delivered at 60–70% lower cost than US/EU providers.

Text & NLP Annotation · India · 2026

Text & NLP Annotation Services in India

99.4% IAA · ₹0.5–₹5 per document · 24-hour turnaround · 100,000+ docs/day

India's most accurate text and NLP annotation service. Expert-annotated NER, sentiment, intent, relation extraction and text classification for AI training datasets.

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📞 +91-9014387222 · contact@dataterminal.co

nlp-tool · text.dataterminal.co

NER · SENTENCE 1 OF 1

Apple Inc. announced that Tim Cook will visit Hyderabad in March 2026 to open a new R&D center.

ORGPERSONLOCATIONDATEFACILITY

Confidence: 0.994 · 5 entities tagged · IAA 99.4%

99.4%IAA Score

24hTurnaround

₹0.5–₹5Per Document

100K+Docs/Day

5+Years Experience

What We Annotate

Every NLP Annotation Type. One Team.

NER, sentiment, intent, relations — expert-annotated at 99.4% IAA, delivered in your format.

Named Entity Recognition

From ₹1/doc

Tag people, organisations, locations, dates, products, and custom entity types. IOB2 format, BERT-compatible offsets.

NLP / NER

Sentiment Analysis

From ₹0.5/doc

Positive, negative, neutral — and aspect-level sentiment per entity. For product reviews, social media, and CX data.

Sentiment AI

Text Classification

From ₹0.5/doc

Single-label and multi-label document classification. Topic, genre, domain, intent category — any taxonomy.

Document AI

Relation Extraction

From ₹3/doc

Label semantic relationships between entities — works-for, located-in, caused-by. Graph-structured annotation output.

Knowledge Graphs

Intent Detection

From ₹1/doc

User intent labels for chatbot and voice assistant training. Slot filling + intent classification in one annotation pass.

Conversational AI

Coreference Resolution

From ₹4/doc

Link pronouns and noun phrases to their referent entities. Essential for document-level understanding in LLMs.

LLM Training

Quality Methodology

How We Hit 99.4% IAA

99.4%

Inter-Annotator Agreement

Industry Average82%

Data Terminal99.4%

Step 01

Domain-Expert Annotators

NLP specialists assigned by vertical — legal, medical, financial, e-commerce. Trained on entity taxonomy before project start.

Step 02

Adjudication Pass

Second annotator reviews every span. Disagreements go to adjudication. IAA computed per batch before delivery.

Step 03

Gold Standard Validation

10% random sample tested against expert-labeled gold documents. Batch fails if IAA drops below 99%.

Step 04

Automated Schema Validation

Every annotation validated against your entity taxonomy. No off-label classes or malformed spans ship.

99.4%

Inter-Annotator Agreement

12+

Languages Supported

Zero

Off-Label Spans Post-QC

Our Process

Upload to Delivery — 24 Hours

Upload

Share text data via secure portal, S3, or API. TXT, CSV, JSONL, PDF — any format. NDA signed on request.

Annotate

Expert annotators work in Label Studio, Prodigy, or your preferred tool. Domain specialists per vertical.

QC Review

IAA computed per batch. Adjudication pass on all disagreements. Gold standard validation before delivery.

Deliver

CoNLL, JSONL, spaCy JSON, Hugging Face format, or any custom schema. IAA report included.

Industries Served

Built for Every Vertical

Domain-expert annotators per industry — not generalists.

⚖️

Legal / Contracts

Clause extraction, party NER, obligation tagging, and risk classification across contracts and legal filings.

NER + Classification

🏥

Healthcare / Clinical

Medical NER for drugs, diagnoses, procedures, and dosages. HIPAA-aware annotators trained on clinical text.

Clinical NLP

🛒

E-commerce

Product attribute extraction, review sentiment, customer intent, and category classification at scale.

Sentiment + Intent

💰

Finance / Banking

Financial entity recognition, sentiment for earnings reports, regulatory document classification.

FinNLP

🎧

Customer Support

Ticket intent classification, escalation entity tagging, and conversation sentiment for CX analytics AI.

Conversational AI

📰

Media / Publishing

News topic classification, quote attribution NER, and named entity disambiguation for media analytics.

Media NLP

Formats & Tools

Works With Your NLP Pipeline

Export Formats

CoNLL-2003JSONLIOB2 TaggingspaCy JSONHuggingFace DatasetCustom Schema

Annotation Tools

Label StudioProdigyDoccanoCVATArgillaCustom API

If your pipeline requires a specific schema or tool integration, we build the connector at no extra cost.

Free Sample Offer

Try Before You Commit

Send us 500 documents. We'll annotate them free in 24 hours — your annotation type, your format, with an IAA report. No payment. No commitment.

500 docs annotatedAny annotation typeYour output formatIAA report included24h delivery

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Free sample on your first project. Response in under 2 hours. Transparent pricing with no hidden costs.

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LocationHITEC City, Hyderabad, India

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