Campus Event Calendar
Event Entry
What and Who
Results of planning for sentence generation
Khansa Rekik
International Max Planck Research School for Computer Science - IMPRS
IMPRS Research Seminar
IMPRS-CS Master Student
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI
Public Audience
English
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Date, Time and Location
Monday, 30 October 2017
12:00
30 Minutes
E1 4
022
Saarbrücken
Abstract
Natural language generation is translated to a planning problem in order to benefit from off-the-shelf planners. The efficiency
of FF and SGPLAN is tested with the sentence generation problem as well as the instruction giving domain and
compared to other conventional tools. Experiments have been made using different configurations. An important amount
of time of the total running time has been allocated to the grounding/parsing step which is not necessarily useful in this
application. To solve this problem for the FF planner, some fixes has been performed. As a first step to make the preprocessing
phase less exhausting, hard processors have been eliminated. Second, action pruning and helpful actions techniques
have been adopted.
of FF and SGPLAN is tested with the sentence generation problem as well as the instruction giving domain and
compared to other conventional tools. Experiments have been made using different configurations. An important amount
of time of the total running time has been allocated to the grounding/parsing step which is not necessarily useful in this
application. To solve this problem for the FF planner, some fixes has been performed. As a first step to make the preprocessing
phase less exhausting, hard processors have been eliminated. Second, action pruning and helpful actions techniques
have been adopted.
Contact
IMPRS-CS Office Team
0681 93251802
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Stephanie Jörg, 10/27/2017 12:59 -- Created document.