Twitter messages are a potentially rich source of continuously and instantly updated information. Shortness and informality of such messages are challenges for Natural Language Processing tasks. In this paper we present a hybrid approach for Named Entity Extraction (NEE) and Classification (NEC) for tweets. The system uses the power of the Conditional Random Fields (CRF) and the Support Vector Machines (SVM) in a hybrid way to achieve better results. For named entity type classification we use AIDA disambiguation system to disambiguate the extracted named entities and hence find their type.
|Title of host publication||Making Sense of Microposts (MSM2013) Concept Extraction Challenge|
|Number of pages||4|
|Publication status||Published - 2013|
- Named Entity Extraction
- Named Entity Classification
- Social Media Analysis
- Twitter Messages