Named Entity Recognition

Named Entity Recognition can identify individuals, companies, places, organization, cities and other various type of entities. API can extract this information from any type of text, web page or social media network.

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Named Entities

You might also be interested in these APIs: Sentiment Analysis, Intent Analysis, Emotion Analysis

Why our named entity extraction API ?

Accurate

ParallelDots NER achieves State-of-the-art results on CoNLL 2003 test dataset with Precision 0.9, Recall 0.92 and F1-Score of 0.90. It uses character as well as word level embeddings and therefore, does not reply on POS labels to detect entities making it very useful to detect entities in user-generated content (Try “obama was the third president of america” in ParallelDots and Spacy)

Fast

ParallelDots NER does not lookup dictionaries like Freebase or DBPedia to identify the type of entities and therefore, is very fast to meet demands from various industries.

Customizable

ParallelDots NER can be customized with very few training examples and therefore, it can be adapted to any domain dataset.

How Our Named Entity Recognition API Works?

Named Entity Recognition API seeks to locate and classify elements in text into definitive categories such as names of persons, organizations, locations. It can extract this information in any type of text, be it a web page, piece of news or social media content.

The API uses Deep Learning technology to determine representations of character groupings.The text to be analyzed is broken into word groups and words are further broken down to character groups and neural network trains on both of these granularities. The hypothesis behind the algorithm is that there are two important aspects which determine if a word is a proper noun, the first is the composition of a word, what syllables it uses and what sounds it comprises of and the second is the adjacent words to the considered word.

use cases

Content Aggregation and Classification

Named Entity Recognition can automatically scan documents and extract important entities like people, organizations, and places. Knowing the relevant entities for each article helps to automatically categorize articles in defined hierarchies as well as enables smooth content discovery.

Customer Support Services

Named Entity Recognition can automatically categorize incoming customer chats into relevant departments based on product names or location names mentioned in them. This can reduce the manual work of support agents and they can take on other complex tasks.

Pricing

(30-day subscription)

Students

Price: $29
3K hits/day
(60 API hits/minute)

Starter

Price: $79
6K hits/day
(60 API hits/minute)

Standard

Price: $199
15K hits/day
(120 API hits/minute)

Business

Price: $299
30K hits/day
(180 API hits/minute)

Advanced

Price: $499
2 Million hits/month
(maximum capacity)

Enterprise

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Checkout our Text Analysis plugins and tool to analyze your textual data without writing any code.

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