This paper presents a toolkit that applies named-entity extraction techniques to identify information related to criminal activity in texts from the Polish Internet. The methodological and technical assumptions were established following the requirements of our application users from the Border Guard. Due to the specificity of the users’ needs and the specificity of web texts, we used original methodologies related to the search for desired texts, the creation of domain lexicons, the annotation of the collected text resources, and the combination of rule-based and machine-learning techniques for extracting the information desired by the user. The performance of our tools has been evaluated on 6240 manually annotated text fragments collected from Internet sources. Evaluation results and user feedback show that our approach is feasible and has potential value for real-life applications in the daily work of border guards. Lexical lookup combined with hand-crafted rules and regular expressions, supported by text statistics, can make a decent specialized entity recognition system in the absence of large data sets required for training a good neural network.

The paper provides an overview of the Polish Speech Database for taking dictation of legal texts, created for the purpose of LVCSR system for Polish. It presents background information about the design of the database and the requirements coming from its future uses. The applied method of the text corpora construction is presented as well as the database structure and recording scenarios. The most important details on the recording conditions and equipment are specified, followed by the description of the assessment methodology of recording quality, and the annotation specification and evaluation. Additionally, the paper contains current statistics from the database and the information about both the ongoing and planned stages of the database development process.