Mapping Natural Language Commands to Web Elements

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Authors Panupong Pasupat, Tian-Shun Jiang, Kelvin Guu, Evan Zheran Liu, Percy Liang
Journal/Conference Name EMNLP 2018 10
Paper Category
Paper Abstract The web provides a rich, open-domain environment with textual, structural, and spatial properties. We propose a new task for grounding language in this environment: given a natural language command (e.g., "click on the second article"), choose the correct element on the web page (e.g., a hyperlink or text box). We collected a dataset of over 50,000 commands that capture various phenomena such as functional references (e.g. "find who made this site"), relational reasoning (e.g. "article by john"), and visual reasoning (e.g. "top-most article"). We also implemented and analyzed three baseline models that capture different phenomena present in the dataset.
Date of publication 2018
Code Programming Language Python
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