Bitext NAMER (Named Entity Recognition)
Bitext NAMER (Named Entity Recognition) is a fundamental component in the realm of natural language processing (NLP) that identifies and categorizes key information within text, such as names of people, organizations, locations, dates, and other entities. At Bitext, our NER services are specifically designed to enhance the capabilities of labeling platforms by providing precise and automated pre-labeling.
This automation allows for the rapid and accurate identification of entities within large datasets, significantly reducing the manual effort required and increasing the overall efficiency of the annotation process. By integrating our Bitext NAMER tools, platforms can ensure that their AI models are trained with high-quality, contextually relevant data, leading to better performance and more reliable outcomes.
How Does Bitext NAMER Work?
Example:
Text: “John lives in New York”
Output:
– John → Person name
– New York → Location
What We Offer with Bitext NAMER
As Software
- SDK: Processes up to 100KB/s of raw text per CPU core.
- Deployment: Available as an on-premise solution or via SaaS API.
As Data
- Dictionaries: Over 100,000 entities per language.
- Annotated Corpora:
- Extracted from public domain sources.
- Custom annotation available upon request for specific models.
Benefits of Bitext NAMER
- Time and Cost Efficiency
- Automates entity recognition, reducing reliance on manual labeling.
- Improved Model Training
- Provides contextually relevant data that optimizes AI model performance.
- Customization
- Enables the creation of tailored corpora for specific industry or business needs.
Key Features
- Entity Coverage:
- Identifies 20 entity types, including: People, places, companies/brands, organizations, account numbers, phone numbers and more.
- Multilingual Support:
- Software and annotated corpora: Available in English, Spanish, French, German, Italian, Portuguese, and Dutch.
- Dictionaries: Supported in 77 languages, offering unparalleled global coverage.
Industries Where Bitext NAMER Adds Value
•Cybersecurity: Detects threats like suspicious accounts, fraudulent emails, and malicious patterns in large datasets.
•Finance: Identifies and categorizes critical data such as accounts and transactions.
•E-commerce: Recognizes brands, products, and key trends.
•Semantic Systems and Knowledge Graphs: Creates semantic relationships between structured and unstructured data.
•Content Management: Analyzes and categorizes large volumes of data for media and communication.
MADRID, SPAIN
Camino de las Huertas, 20, 28223 Pozuelo
Madrid, Spain
SAN FRANCISCO, USA
541 Jefferson Ave Ste 100, Redwood City
CA 94063, USA