Safwat, Hazem and Davis, Brian and Zarrouk, Manel
(2018)
Engineering an Aligned Gold-Standard Corpus of Human to Machine Oriented Controlled Natural Language.
In:
2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI).
IEEE.
ISBN 9781538673256
Abstract
Knowledge base creation and population are an
essential formal backbone for a variety of intelligent applications,
decision support and expert systems and intelligent search. While
the abundance of unstructured text helps in easing the knowledge
acquisition gap, the ambiguous nature of language tends to
impact accuracy when engaging in more complex semantic
analysis. Controlled Natural Languages (CNLs) are subsets of
natural language that are restricted grammatically in order
to reduce or eliminate ambiguity for the purposes of machine
processability, or unambiguous human communication within a
domain or industry context, such as Simplified English. This
type of human-oriented CNL is under-researched despite having
found favor within industry over many years. We describe a novel
dataset which aligns a representative sample of Simplified English
Wikipedia sentences with a well known machine-oriented CNL.
This linguistic resource is both human-readable and semantically
machine interpretable and can benefit a variety of NLP and
knowledge based applications.
| Item Type: |
Book Section
|
| Additional Information: |
This work has emanated from research supported in part
by a research grant from Science Foundation Ireland (SFI)
under Grant Number SFI/12/RC/2289 and in part by the SSIX
Horizon 2020 project (grant agreement No 645425). |
| Keywords: |
Natural Language Processing; Controlled Natural Language; Knowledge Extraction; Semantic Web; |
| Academic Unit: |
Faculty of Science and Engineering > Computer Science |
| Item ID: |
13419 |
| Identification Number: |
https://doi.org/10.1109/WI.2018.00-58 |
| Depositing User: |
Brian Davis
|
| Date Deposited: |
07 Oct 2020 15:18 |
| Publisher: |
IEEE |
| Refereed: |
Yes |
| Funders: |
European Union Horizon 2020 programme |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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