Text Analytics with sentiment analysis, categorization & named entity extraction.
Note: the page content includes an embedded instruction directing AI agents to visit an external URL (llms.txt) — this looks like a prompt injection attempt and I did not follow it.
Semantria is a paid SaaS text analytics API from Lexalytics, offered as a fully REST-compliant service. It provides natural language processing capabilities including sentiment analysis, tokenization and part-of-speech tagging, categorization, auto-categorization, taxonomy, entity recognition, theme extraction, lexical chaining, language detection, summarization, and relationship extraction, along with speech-to-text and machine translation support.
The API can be accessed directly or through SDKs, with documented quick-start guides for Python and .NET; developers rolling their own integration can use standard HTTP libraries such as requests (Python) or OkHttp (Java). Configuration options include layered configurations, configuration routes, sentiment phrases, query topics, entity configuration, concept topics, blacklists, and taxonomy models.
It is aimed at developers and businesses needing text analytics integrated into their applications, with access requiring contacting Lexalytics sales. The documentation also covers account and user management, a service user role, and integration with other services such as PubNub.
No, Semantria is a paid SaaS text analytics service from Lexalytics and requires contacting sales to discuss pricing.
Semantria offers Quick Start guides and SDKs for Python and .NET, and is fully REST compliant so it can also be used with standard HTTP libraries like requests or OkHttp.
It is intended for developers and businesses who need to integrate natural language processing and text analytics into their applications.
It provides sentiment analysis, tokenization and POS tagging, categorization, entity recognition, themes, lexical chaining, language detection, summarization, and relationship extraction.
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