Event Extraction

NetOwl Extractor offers one-of-a-kind event extraction capabilities in addition to entity extraction and relationship extraction. NetOwl can be deployed on premises or in the cloud, enabling a variety of Big Data Text Analytics applications.

Extensive Ontology for Event Extraction

NetOwl offers an extensive semantic event ontology out of the box that is applicable to many domains. An event typically contains one or more participants and often is associated with a particular time or place. NetOwl’s event extraction not only extracts the events themselves but also the event participants. This truly unique rich event extraction is supported by NetOwl’s entity extraction with its broad entity ontology.

NetOwl’s event ontology provides over 100 types of events. Sample events include transactions, conflicts, mergers and acquisitions, personnel events, etc.

Event Extraction and Event Participants

NetOwl not only extracts events but also identifies the event participants. For example, NetOwl can identify multiple event participants with their distinct roles for a given event – an “arrest” event may involve the person arrested, the entity that made the arrest, and the time and location of the arrest.

Event extraction with participant information allows users to gain unparalleled insight from a large collection of text data: companies acquired or acquiring other companies last year, places a given person traveled to in the last month, the number of attacks that happened in a particular city in the month of August, etc.

Connecting Event Participants

For successful event extraction, connecting non-name mentions (pronouns and definite noun phrases) to name mentions is crucial. NetOwl not only extracts named entities (e.g., “Mary Smith”) but also descriptive noun phrases (e.g., “the CEO”) for each entity ontology type. Additionally, NetOwl connects anaphors such as pronouns (“she”) and definite noun phrases (“the company”) to corresponding named entities through its advanced co-reference resolution capability. Together, NetOwl makes sense out of a sentence like “The company announced today that she will be become the next CEO,” extracting a personnel change event with a particular company and person as the event participants.

Event Extraction for Cyber Security

NetOwl’s Cyber Security ontology adds Cyber Security-specific semantic entity and event types to NetOwl’s entity and event ontologies. It integrates critical cyber-related concepts from US-CERT, Department of Defense, and other leading cyber security organizations.

Sample cyber entities and events include malware and hacking tools along with denial of service attacks, phishing, website hijacking, etc. With the addition of the Cyber Security ontology, organizations can monitor and analyze ever evolving cybercrime incidents effectively.

Key Features of Event Extraction

High Accuracy & Speed

Provides state-of-the-art event 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

REST APIs offer easy integration. Pre-integrated with popular search and analytics tools like Elasticsearch and Esri ArcGIS.
Coreference Resolution
Resolves co-referring entities, whether they are names, pronouns, definite noun phrases, or events:
- “the technology company” ➞ “Apple”
Customizable

Creator Edition (CE) enables the customization of entities, relationships, and events.
Multilingual

Event extraction currently available in English and Arabic. Other languages are on the way.

Extensive Ontology for Event Extraction

Event Extraction and Event Participants

Connecting Event Participants

Event Extraction for Cyber Security

Key Features of Event Extraction

High Accuracy & Speed

On Premise or in the Cloud

Easy Integration

Coreference Resolution

Customizable

Multilingual