Common problem:

Processing data usually means wasting time and losing valuable information

Nowadays, there is a frequent need to extract trends and other relevant information from large collections of text (social media, online reviews, etc.) fast and accurately. However, when dealing with unstructured “messy” data, it is not easy to extract meaningful information.


Phrase Extraction helps you providing a comprehensive analysis of your data

Bitext Phrase Extraction service allows you to go beyond hashtags or keywords, no matter if it’s for high-quality texts, like news or legislation, or for colloquial ones, like blogs or social media. Additionally, it extracts the type of phrase: noun, verb, adjective or adverb phrase.

Entity Extraction

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Detect Key topics, ideas and trends

Our linguistic expertise makes our phrase extraction unique to provide more accurate and less noisy input out of your raw data.

Extract information for multiple purposes:

  • General information to build Knowledge Graphs

  • Extract topics like nouns to enhance Topic Modelling

  • Relations between topics, for example noun phrases via verbs


Extracts and classifies different types of phrases

The phrase extraction service detects and extracts:

  • Simple phrases: “checking account”, “twin brother”

  • Compound or nested phrases: “my brother’s checking account”

  • Combinations of the above: “account”, “checking account”, “checking account of the bank”, “bank”, “my brother’s bank”

  • E-mail addresses, URLs, social media users and hashtags

Normalizes variants into standard forms

The phrase extraction service applies a normalization process to the phrases in order to coherently handle all instances of the same phrase. As an example the following phrases are instances of the same concept:

  • “The checking account”

  • “These checking accounts”

  • “One of my checking accounts”

A correct normalization of concepts is essential for services such as categorization or for trend detection.

If you want additional info schedule your demo

bitext madrid offices


José Echegaray 8, building 3, office 4
Parque Empresarial Las Rozas
28232 Las Rozas

san francisco bitext offices


541 Jefferson Ave., Ste. 100
Redwood City
CA 94063