Lee-Krahmer-Wubben Data-To-Text Generation Task

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A Lee-Krahmer-Wubben (LKW) Data-To-Text Generation Task is a Data-to-Text Generation Task that generates text items using templatized data representations.

Corpus Retrieval SMT NMT
Templates

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Templates

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Direct Templates

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Templatess

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Direct Templates

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Templates

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Direct
Weather.gov 63.94 34.52 69.57 89.29 36.56 61.92 89.85 36.93 78.90
Prodigy-METEO 44.47 27.65 23.66 39.32 26.15 30.37 45.03 26.52 27.82
Robocup 31.39 30.73 22.38 40.77 38.18 39.04 38.98 36.62 37.50
DutchSoccer 2.49 1.65 4.99 1.64 0.90 2.10 1.95 1.23 1.70
Retrieval SMT NMT
Corpus Templates Direct Templates Direct Templates Direct
Fluency Weather.gov 4.08(1.04) 5.32(0.88) 5.24(0.95) 4.76(0.79) 5.00(0.97) 5.50(1.02)
Prodigy-METEO 3.27(1.13) 2.81(1.14) 2.99(1.16) 3.02(1.13) 3.31(1.47) 3.27(1.43)
Robocup 5.21(0.99) 5.46(1.05) 5.70(0.99) 4.82(1.20) 5.59(1.04) 5.67(1.11)
Dutch Soccer 4.12(0.99) 5.33(0.91) 2.11(0.97) 1.78(0.85) 6.10(0.84) 5.73(0.84)
Clarity Weather.gov 4.36(1.14) 5.52(0.99) 5.45(1.02) 5.24(1.02) 5.13(1.26) 5.69(1.04)
Prodigy-METEO 2.94(1.24) 2.73(1.26) 2.82(1.27) 2.96(1.16) 3.25(1.57) 3.29(1.47)
Robocup 5.59(0.96) 5.73(1.03) 5.96(0.92) 5.11(1.22) 5.84(0.98) 5.78(1.37)
Dutch Soccer 4.85(1.16) 5.52(0.90) 2.43(0.99) 1.94(0.90) 6.10(0.92) 5.74(0.83)
Correctness Weather.gov 3.34(0.91) 3.92(0.90) 2.55(0.90) 2.70(1.04) 4.03(1.04) 3.22(1.26)
Prodigy-METEO 4.17(1.22) 3.21(0.97) 3.88(1.23) 3.72(1.20) 3.99(1.18) 3.56(0.88)
Robocup 5.06(1.14) 3.83(1.08) 5.78(1.08) 5.23(1.13) 5.70(1.09) 5.68(0.92)
Dutch Soccer 3.34(0.91) 3.92(0.90) 2.55(0.90) 2.70(1.04) 4.03(1.04) 3.22(1.26)


References

2018a

2018 AutomatedLearningofTemplatesfor Fig1.png
Figure 1: Direct method of data-to-text conversion.

2018 AutomatedLearningofTemplatesfor Fig2.png
Figure 2: Templatization method of data-to-text conversion.

2018b

2017

(Klein et al., 2017)Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander M. Rush. (2017)."OpenNMT: Open-Source Toolkit for Neural Machine Translation". In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017) System Demonstrations.

2012

2007