Abstract
I present an architecture for data-to-text systems, that is NLG systems which produce texts from non-linguistic input data; this essentially extends the architecture of Reiter and Dale (2000) to systems whose input is raw data instead of AI knowledge bases. This architecture is being used in the BabyTalk project, and is based on experiences in several projects at Aberdeen; it also seems to be compatible with many data-to-text systems developed elsewhere. It consists of four stages which are organised in a pipeline: Signal Analysis, Data Interpretation, Document Planning, and Microplanning and Realisation.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Eleventh European Workshop on Natural Language Generation (ENLG 07) |
| Editors | Stephan Busemann |
| Place of Publication | Stroudsburg |
| Publisher | Association for Computational Linguistics |
| Pages | 97-104 |
| Number of pages | 8 |
| Publication status | Published - 2007 |
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Dive into the research topics of 'An Architecture for Data-to-Text Systems'. Together they form a unique fingerprint.Impacts
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Mainstream communication of big data using natural language generation (NLG)
Ehud Reiter (Coordinator) & Gowri Sripada (Coordinator)
Impact: Economic and/or Commercial