Text Annotation services

What is Text annotation?

Text annotation helps machine learning models understand text data. Common workflows that utilize text annotation include sentiment and intent analysis, part-of-speech tagging, entity recognition and classification. During the text annotation process, the data is parsed into the required categories including phrases, sentences, and keywords, based on the guidelines of the project. The annotated datasets train machines to communicate efficiently in the natural language of humans. Text annotation can be used in the creation of training data to improve the performance of search engines, build chatbots, design a question answering system, help students improve their reading comprehension, facilitate translation of text from one language to another, and so much more. Text annotation can also be combined with image annotation to train multimodal machine learning models.

What are the types of Text annotation?

iMerit provides various text annotation services that cater to a client’s project needs. Common workflows include sentiment analysis, intent analysis, named entity recognition (NER), natural language processing (NLP) and entity classification. iMerit’s team works with clients to calibrate their quality and throughput requirements and builds custom processes to support client needs and integrate with their existing workflows. iMerit’s teams deliver the highest quality results of cost-effective human language text annotation across batches and iterations. We recommend running a sample batch to clarify instructions, edge cases, and approximate task times, before launching full batches.

iMerit’s Text annotation Services

Sentiment Analysis

iMerit’s advanced sentiment and topic analysts can identify trends and nuances in large volumes of text data including product reviews, financial news, and social media. Useable in any language, annotation for sentiment analysis enables companies to better understand how their customer bases view their products, which way a stock price may be trending, identify unsolved customer needs, and more.

Intent Analysis

iMerit text annotation experts bring the building blocks of NLU together to drive the development of next-generation chatbots, digital assistants, and conversational AI products in retail, tech media, finance, and healthcare.

NAMED ENTITY RECOGNITION (NER) & ENTITY CLASSIFICATION

By identifying, classifying, underlining, and linking relevant text and metadata strings, iMerit powers innovations in digital document analysis, conversational AI development, and knowledge base curation.

Natural language processing

Understand the sentiment between the lines of text. Glean valuable insights to improve things like search relevance and improve automated chat systems that are commonly employed in customer service.

Image annotation

Add iMerit’s image annotation services to your existing (or iMerit provided) text annotation workflow to train models that operate jointly on images and text. Useful for intelligent document processing (IDP), generating better word embeddings, image summarization, logo and product identification + recognition, and more.

Rapid annotation

iMerit annotation experts create best-in-class text training datasets in rapid time for any AI or ML project.

Text annotation
process

iMerit subject matter experts will guide you through the process to develop a customized end-to-end workflow.

1

EXPERT CONSULTATION

Transformative, solution-based approach. Interdisciplinary Text Annotation problem solving. Agility and responsiveness, Time-To-Value enhancers.

2

TRAINING

Targeted resources. Custom skilling. Focused and deep microlearning curriculum. Domain expertise. Rostering tools.

3

WORKFLOW CUSTOMIZATION

Alignment of Text Annotation tools and processes. Structured Development Milestones. Two-step production and QA annotation workflows.

4

FEEDBACK CYCLE

Transparency via analytics. Real Time Monitoring and Service Delivery Insights. Edge case Insights. Dynamic Model Improvement.

5

EVALUATION

Assessment of deliverable. Appraisal of key metrics, quality control processes. Model reconsideration. Analysis of business outcome.

Talk to an expert

What industries need Text annotation?

Medical AI

Text annotation helps to turn a healthcare database into valuable insights. These insights can improve patient outcomes, streamline operations, and manage regulatory compliance.

Legal

Automatically review contracts, extract dates and key information, and speed up case law searches. The legal industry is replete with large, often inscrutable and highly technical documents that require tens of thousands of man hours to process. Text annotation provides the first step towards automating this process and saving valuable time.

Finance

Text annotation workflows can transform complex documents into intelligence that leads to a better customer experience.

Government

Teams trained in domain-specific lexicons work on linguistic projects to extract intelligence from vast government records and datasets to enable automation of processes.

Commerce

Text annotation in commerce helps to analyze the sentiment and intent within customer reviews and comments, and to mine useful information from unstructured data to improve customer experience for shoppers.

Insurance

Insurance companies are using text annotation to extract details contained in application forms, adjuster notes, and other unstructured text sources, to minimize their risk and improve efficiency.

Social Media

Social media platforms are full of valuable consumer stories and opinions but are filled with acronyms, complex abbreviations, and emoticons. Text annotation helps to transform this into structured data and provides useful insights.

Biomedical

Text annotation can identify key entities such as proteins, medications, genes, chemicals, and diseases, facilitating searches of large pharmaceutical libraries or databases of genes and proteins connected to cancer.

Product Marketing

When combined with language modeling and generation, text annotation can be used in systems which generate slogans and marketing copy.

Text annotation use cases

Text annotation solution for Taxation data

CrowdReason has huge volumes of taxation data from its client base. These data vary across geographies, and tax jurisdictions, that need to be processed and structured quickly and accurately. iMerit’s experts have developed a workflow to break down the data extraction process into smaller tasks. These tasks are tackled by iMerit’s trained text annotation teams.

“iMerit was and continues to be, an invaluable partner for us. They provided us with accurate data early on, which helped us get up and running with the development of our tax property software.” — Brandon Van Volkenburgh, CTO & Co-founder, CrowdReason

Text Annotation solution for linguistic datasets

iMerit’s customer provides a service that helps subscribers improve the quality of their writing by correcting mistakes and providing word and phrase suggestions. The company needed multiple wording suggestions to confirm and refine a sentence correction algorithm. The challenge was in balancing the subjective and nuanced nature of copy-editing with the need for a rule-based style standardization. Our text annotation teams were trained rigorously in the customer’s style guide. Continuous assessment and peer learning, along with close collaboration with the customer in areas of ambiguity enables the team to deliver high-quality stylistic, structural, and mechanical corrections on a variety of document sources.

Text ANNOTATION IN NUMBERS

20

Mn

Text data points Annotated

97

%

Accuracy

Learn more about text annotation

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CrowdReason’s Quality Model Uses iMerit Labeled Data

Annotating Data for Natural Language Processing

Get Started with text Annotation

The need for speed in high-quality text annotation has never been greater. iMerit combines the best predictive and automated annotation technology with world-class data annotation and subject matter experts to deliver the data you need to get to production, fast.