Towards Czech Answer Type Analysis
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2018 |
| MU Faculty or unit | |
| Citation | |
| Web | https://nlp.fi.muni.cz/raslan/2018/paper13-Kusnirakova_Medved.pdf |
| Keywords | question answering; question classification; answer classifica-tion; Czech; Simple Question Answering Database; SQAD |
| Description | In this paper, we introduce two answer type detection systems for Czech language. Based on the input question, the goal of these tools is to recognise the question type and extract an appropriate answer type. Except for the same goal, these systems are completely different. The first one is a rule based system utilising Czech Wordnet for hypernym detection. The second one uses a machine learning approach in form of a neural network. We present architectures of these two systems and offer a detailed evaluation on more than 8,500 question-answer pairs using the SQAD v2.1 benchmark dataset. |
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