论文信息 - SUMTIME-METEO: Parallel Corpus of Naturally Occurring Forecast Texts and Weather Data

SUMTIME-METEO: Parallel Corpus of Naturally Occurring Forecast Texts and Weather Data

In this report, we describe SUMTIME-METEO, a parallel corpus of naturally occurring weather data and their corresponding forecast texts. The corpus has 1045 parallel data-text units and is available both as raw data in the form of ASCII files and also as a Microsoft Access database.

Somayajulu Sripada | Jin Yu | Ian P. Davy | Wni Oceanroutes

[1] Jim Hunter,et al. Modelling the Task of Summarising Time Series Data Using KA Techniques , 2002 .

[2] A. Carlisle Scott,et al. Practical guide to knowledge acquisition , 1991 .

[3] John Cocke,et al. A Statistical Approach to Machine Translation , 1990, CL.

[4] Ehud Reiter,et al. Learning the Meaning and Usage of Time Phrases from a Parallel Text-Data Corpus , 2003, HLT-NAACL 2003.

[5] Ehud Reiter,et al. Should Corpora Texts Be Gold Standards for NLG? , 2002, INLG.

[6] Ehud Reiter,et al. S UM T IME : Observations from KA for Weather Domain , 2001 .

[7] Jim Hunter,et al. Segmenting Time Series for Weather Forecasting , 2003 .