LingRep - Technology
LingRep - The Language Technology Behind

It's there. Let's discover!



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LingRep (LINGuistic REPository) is an innovative text analytics framework that comprehensively enables outsourcing of complex linguistic functionalities in software products. This leverages the application focus on business value while benefiting from premium quality text analytics in the background.





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LingRep analysis can be applied to any domain and application area. The key to success resides in tailoring the analysis exactly to the application goals and needs. It includes the configuration of each single analysis component based on parameters and the underlying data, which is derived from the huge LingRep database or external sources such as DBpedia or Freebase. If exists, customer data and even linguistic functionalities can also be integrated in the LingRep analysis services.





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These adaptations are optimally supported by the highly qualified team of LingRep experts that consult and support your visions throughout all phases of the development process, ranging from requirements elicitation to the maintenance of the final software product. As a matter of course, customer configurations and customer data always remain the intellectual property of the customer!








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econob understands its own role as an innovative solution partner, being only successful if their partners with their solutions are successful!






ValueChain

 
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Language Independency is a core feature of the LingRep technology. The framework currently offers processing of both English and German. However, LingRep is extendable to support any other language as well.

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Structural Analysis identifies building blocks such as titles, paragraphs, listings, and sentences in natural language texts. It serves as foundation for all subsequent processing steps and allows for elaborated passage interpretation.

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Semantic Analysis is concerned with the recognition of named entities. All named entities (e.g., locations, companies, persons) and their interrelations are provided by the LingRep ontology enabling hierarchical abstraction, navigation, and filtering.

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Event Detection links semantically related material into meaningful propositions possibly involving multiple named entities, verbs and patterns. The identification of such relations from natural language text together with their anchoring in the timeline provides unforeseen opportunities.

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Orientation Assessment quantifies the different semantic traits of a natural language text. It can be understood as a generalized model of the well known sentiment analysis, capable of capturing more advanced traits such as subjectivity/objectivity, precision and confidence. In order to determine customer-based text interpretations, new models are frequently developed.
























 

Each of the processing steps above adds a single piece to the overall quality of the text analytics. It is the combination that makes the difference!