All Outputs (5)

The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes (2016)
Conference Proceeding
Bartie, P., Mackaness, W., Gkatzia, D., & Rieser, V. (2016). The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes. In 10th International Conference on Language Resources and Evaluation (LREC)

We present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchored Language). The REAL corpus contains a collection of images of real-world... Read More about The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes.

How to Talk to Strangers: generating medical reports for first time users (2016)
Conference Proceeding
Gkatzia, D., Rieser, V., & Lemon, O. (2016). How to Talk to Strangers: generating medical reports for first time users. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ-IEEE.2016.7737739

We propose a novel approach for handling first-time users in the context of automatic report generation from timeseries data in the health domain. Handling first-time users is a common problem for Natural Language Generation (NLG) and interactive... Read More about How to Talk to Strangers: generating medical reports for first time users.

Content Selection in Data-to-Text Systems: A Survey (2016)
Working Paper
Gkatzia, D. (2016). Content Selection in Data-to-Text Systems: A Survey

Data-to-text systems are powerful in generating reports from data automatically and thus they simplify the presentation of complex data. Rather than presenting data using visualisation techniques, data-to-text systems use natural (human) language , w... Read More about Content Selection in Data-to-Text Systems: A Survey.

The REAL corpus (2016)
Dataset
Bartie, P., Mackaness, W., Gkatzia, D., & Rieser, V. (2016). The REAL corpus. [Dataset]

Our interest is in people’s capacity to efficiently and effectively describe geographic objects in urban scenes. The broader ambition is to develop spatial models capable of equivalent functionality able to construct such referring expressions. To th... Read More about The REAL corpus.

Natural Language Generation enhances human decision-making with uncertain information. (2016)
Conference Proceeding
Gkatzia, D., Lemon, O., & Rieser, V. (2016). Natural Language Generation enhances human decision-making with uncertain information. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (264-268). https://doi.org/10.18653/v1/P16-2043

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different information presentations for uncertain data and, for the first time, measure their effects on hu... Read More about Natural Language Generation enhances human decision-making with uncertain information..