Entity Extraction Software

Entity extraction (aka named entity recognition or NER) finds entities such as person, place, organization, and product names in text using AI-based natural language processing and machine learning technologies. NetOwl offers highly accurate, fast, and scalable entity extraction in multiple languages.

Why is Entity Extraction Challenging?

Entity extraction needs to address different types of challenges due to the flexibility and ambiguity that characterizes human languages:

Creativity: Humans are constantly creating new words and names for companies, products, and even personal and place names.
Entity Type Ambiguity: The same name may refer to entities of different types depending on context.
Part of Speech Ambiguity: The same word may have multiple grammatical functions depending on context. For instance, “may” can be a first name (May Stevens), a last name (Tom May), a month (May), and an auxiliary (may happen).
Semantic Ambiguity: The same word may have different meanings that result in an ambiguous context for Entity Extraction. For example, the noun “operator” could denote a person (crane operator Chris Johnson), organization (tour operator XYZ Adventure), or a function in programming (logical operator XOR).
Noisy Text: Unlike well-edited texts such as newspaper articles, informal language, which is common in social media, email, and texting, often contains typos and misspellings, lacks proper capitalization and punctuation, and may not be grammatical. Also, sources like OCR and ASR output frequently contain errors.

NetOwl entity extraction addresses these entity extraction challenges with high accuracy, speed, and scalability.

Extensive Ontology for Entity Extraction

With over 100 types of entities, NetOwl entity extraction offers a broad semantic ontology that goes beyond that of standard named entity extraction software. It includes people, various types of organizations (e.g., companies, governments), several types of places (e.g., countries, cities), addresses, artifacts, phone numbers, titles, etc. This expansive named entity recognition forms the foundation for more advanced relationship extraction and event extraction.

Domains include Business, Finance, Politics, Homeland Security, Law Enforcement, Military, National Security, and Social Media.

Multilingual Entity Extraction

NetOwl supports entity extraction in multiple languages, including English, Arabic, Chinese (traditional and simplified), French, German, Korean, Persian (Farsi and Dari), Russian, and Spanish. The same comprehensive entity ontology available in English is also available for all the other languages, making multilingual and cross-lingual text analytics applications easier to develop.

Name Normalization

NetOwl not only performs entity extraction but also assigns normalized forms to extracted person, organization, and place names, taking into account capitalization, acronyms, abbreviations, nicknames, etc. When Smart Geotagging is used, place names are both disambiguated and normalized. Name normalization is ideal for cross-document name resolution for applications such as faceted search, and various forms of intelligence analysis such as geospatial analysis and link analysis.

NetOwl integrates easily with many popular search, geospatial, and business intelligence tools such as Elasticsearch, Solr, MarkLogic, Esri ArcGIS, Tableau, Kibana, etc.

Smart Name Translation

NetOwl Extractor’s Smart Name Translation provides English translation of named entities extracted from foreign language texts that use different alphabets/scripts, for example, Arabic, Chinese (traditional and simplified), Korean, Persian (Farsi and Dari), and Russian. Smart Name Translation gives an effective way for monolingual users to search and gist foreign language content.

Key Features of Entity Extraction

High Accuracy & Speed

Provides state-of-the-art entity extraction accuracy on many different types of text. Extremely fast and scalable for real-time analysis.
On Premise or In the Cloud

Supports Docker and Kubernetes for easy and scalable deployment.
Easy Integration

An easy-to-integrate entity extraction tool with a REST API. Pre-integrated with popular search and analytics tools like Elasticsearch and Esri ArcGIS.
Coreference Resolution
Resolves co-referring entities, whether they are name aliases or acronyms:
- “Ms. Smith” ➞ “Mary Smith”
- “FAA” ➞ “Federal Aviation Administration”
Customizable

Creator Edition (CE) enables the customization of existing entity types or addition of new entity types.
Language ID

A seamlessly integrated language ID module detects the language of the input text automatically and performs entity extraction accordingly.