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NLP Pipeline

large-scale, parallel, multilingual and modularized

Multilingual text processing has never been so easy. Our Natural Language Processing pipeline is made of parallel, independent modules that make it possible to perform tasks like language recognition, tokenization, morphological analysis, part-of-speech tagging, lemmatization and named entity recognition.

NLP Pipeline header logo

Modules

Named Entity Recognition

NER locates and classifies named entities mentioned in unstructured text into predefined categories, such as person names, organizations, locations, and more. This module helps identify and categorize critical information within large text datasets, facilitating better data organization and retrieval.

Named Entity Recognition base layerNamed Entity Recognition illustration

Emotion and Sentiment Analysis

This module identifies language abuse and detects and tags emotions from text. It goes beyond simple sentiment analysis by determining who feels the emotion, towards whom, and why. This advanced capability allows for a deeper understanding of the emotional context within the text.

Emotion and Sentiment Analysis base layerEmotion and Sentiment Analysis illustration

Word Sense Disambiguation

WSD involves identifying the correct meaning of a word based on its context. Our WSD capabilities ensure that every word is interpreted accurately, reducing ambiguities and enhancing the clarity and relevance of processed information. This module is essential for understanding the true intent and meaning behind words in diverse contexts.

Word Sense Disambiguation base layerWord Sense Disambiguation illustration

Entity Linking

Entity Linking connects mentions of entities within the text to their corresponding entries in a knowledge base. Our entity linking module ensures accurate identification and contextual understanding of names, places, organizations, and other entities, enhancing the depth and accuracy of text analysis.

Entity Linking base layerEntity Linking illustration

Morphological analysis

The morphological analysis module provides detailed information about the inflection of words, such as the tense of a verb or the gender and number of a noun. Its lemmatization capability reduces the inflectional forms of a word to a common base form, or lemma, ensuring consistency and accuracy in text processing.

Morphological analysis base layerMorphological analysis illustration

Language Detection

Babelscape’s language detector can identify 60 languages, including all European languages and most Asian languages. This module ensures accurate language recognition, enabling seamless processing and analysis of multilingual text data.

Language Detection base layerLanguage Detection illustration
Abstract Modules representationNamed Entity Recognition illustrationEmotion and Sentiment Analysis illustrationWord Sense Disambiguation illustrationEntity Linking illustrationMorphological analysis illustrationLanguage Detection illustration

Our multilingual NLP Pipeline is designed with a modular architecture that allows for unparalleled flexibility and efficiency.

It can be tailored to meet your specific needs, accessing each tool separately or leveraging the full suite for comprehensive analysis.

AVAILABLE ONLINE AND OFFLINE
  • Language recognition
  • Tokenization
  • Morphological analysis
  • Part-of-speech tagging
  • Named entity recognition
  • Word Sense Disambiguation
  • Entity Linking
  • Domain labeling
  • Term, concept and entity extraction
  • Sentiment analysis
AVAILABLE OFFLINE
  • Tag classification
  • Semantic vector document creation
  • Semantic document similarity of sentences, paragraphs and documents
NLP Pipeline modules illustration

Features

Babelscape’s NLP pipeline comes with several groundbreaking features. It is designed to work on a large scale in dozens of languages using the same interface for each language. Users can choose only the modules they need and can run dozens of tasks in parallel on the same CPU.

The pipeline also integrates our flagship products as modules: WordAtlas, Comprehendo and Extraggo, thanks to which a full-fledged analysis of text can be performed, ranging from tokenization to semantic analysis and text analytics.

Multilinguality

Large scale

Parallel

Modularity

Flexible

High performance

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