A Hierarchical Model for Data-to-Text Generation

20 Dec 2019Clément RebuffelLaure SoulierGeoffrey ScoutheetenPatrick Gallinari

Transcribing structured data into natural language descriptions has emerged as a challenging task, referred to as "data-to-text". These structures generally regroup multiple elements, as well as their attributes... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Data-to-Text Generation RotoWire Hierarchical transformer encoder + conditional copy BLEU 17.50 # 1
Data-to-Text Generation RotoWire (Content Ordering) Hierarchical Transformer Encoder + conditional copy DLD 18.90% # 1
Data-to-Text Generation Rotowire (Content Selection) Hierarchical Transformer Encoder + conditional copy Precision 39.47% # 1
Recall 51.64% # 1
Data-to-Text Generation RotoWire (Relation Generation) Hierarchical Transformer Encoder + conditional copy count 21.17 # 3
Precision 89.46% # 1

Methods used in the Paper


METHOD TYPE
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