BOLT English SMS/Chat
| Item Name: | BOLT English SMS/Chat |
| Author(s): | Song Chen, Dana Fore, Stephanie Strassel, Haejoong Lee, Jonathan Wright |
| LDC Catalog No.: | LDC2018T19 |
| ISBN: | 1-58563-856-0 |
| ISLRN: | 204-077-773-055-9 |
| DOI: | https://doi.org/10.35111/hkfc-7865 |
| Release Date: | August 15, 2018 |
| Member Year(s): | 2018 |
| DCMI Type(s): | Text |
| Data Source(s): | text chat conversations |
| Project(s): | BOLT |
| Application(s): | machine translation |
| Language(s): | English |
| Language ID(s): | eng |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2018T19 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Chen, Song, et al. BOLT English SMS/Chat LDC2018T19. Web Download. Philadelphia: Linguistic Data Consortium, 2018. |
| Related Works: | View |
Introduction
BOLT English SMS/Chat was developed by the Linguistic Data Consortium (LDC) and consists of naturally-occurring Short Message Service (SMS) and Chat (CHT) data collected through data donations and live collection involving native speakers of English. The corpus contains 18,429 conversations totaling 3,674,802 words across 375,967 messages.
The BOLT (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference.
Data
The data in this release was collected using two methods: new collection via LDC's collection platform and donation of SMS or chat archives from BOLT collection participants. All data collected were reviewed manually to exclude any messages/conversations that were not in the target language or that had sensitive content, such as personal identifying information (PII). All data is presented in UTF-8 XML.
Acknowledgement
This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Samples
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Updates
None at this time.