Summary of the paper
| Title | MACAQ : A Multi Annotated Corpus to Study how we Adapt Answers to Various Questions |
|---|---|
| Authors | Anne Garcia-Fernandez, Sophie Rosset and Anne Vilnat |
| Abstract | This paper presents a corpus of human answers in natural language collected in order to build a base of examples useful when generating natural language answers. We present the corpus and the way we acquired it. Answers correspond to questions with fixed linguistic form, focus, and topic. Answers to a given question exist for two modalities of interaction: oral and written. The whole corpus of answers was annotated manually and automatically on different levels including words from the questions being reused in the answer, the precise element answering the question (or information-answer), and completions. A detailed description of the annotations is presented. Two examples of corpus analyses are described. The first analysis shows some differences between oral and written modality especially in terms of length of the answers. The second analysis concerns the reuse of the question focus in the answers. |
| Topics | Corpus (creation, annotation, etc.), Question Answering |
Full paper |
MACAQ : A Multi Annotated Corpus to Study how we Adapt Answers to Various Questions |
Slides |
MACAQ : A Multi Annotated Corpus to Study how we Adapt Answers to Various Questions |
| Bibtex | @InProceedings{GARCIAFERNANDEZ10.301, author = {Anne Garcia-Fernandez and Sophie Rosset and Anne Vilnat}, title = {MACAQ : A Multi Annotated Corpus to Study how we Adapt Answers to Various Questions}, booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |