TDT5 Multilingual Text
| Item Name: | TDT5 Multilingual Text |
| Author(s): | David Graff, Junbo Kong, Kazuaki Maeda, Stephanie Strassel |
| LDC Catalog No.: | LDC2006T18 |
| ISBN: | 1-58563-417-4 |
| ISLRN: | 492-763-586-162-2 |
| DOI: | https://doi.org/10.35111/azvq-yv94 |
| Release Date: | December 19, 2006 |
| Member Year(s): | 2006 |
| DCMI Type(s): | Text |
| Language(s): | English, Mandarin Chinese, Standard Arabic |
| Language ID(s): | eng, cmn, arb |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2006T18 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Graff, David, et al. TDT5 Multilingual Text LDC2006T18. Web Download. Philadelphia: Linguistic Data Consortium, 2006. |
| Related Works: | View |
Introduction
The TDT5 corpora were created by Linguistic Data Consortium with support from the DARPA TIDES (Translingual Information Detection, Extraction and Summarization) Program. This release contains the complete set of English, Arabic and Chinese newswire text used in the 2004 Topic Detection and Tracking technology evaluations. The topic relevance annotations corresponding to this publication can be found in LDC Publication LDC2006T19, TDT5 Topics and Annotations.
Topic Detection and Tracking (TDT) refers to automatic techniques for finding topically related material in streams of data such as newswire and broadcast news.
There were four TDT tasks defined for the 2004 evaluation: the tracking of known topics, the detection of unknown topics, the detection of initial stories on unknown topics, and the detection of pairs of stories on the same topic (links). Of these four tasks, the topic tracking task and the link detection task are considered to be "primary." Previous TDT evaluations also included a story segmentation task. This task applied only to broadcast news. Since TDT5 does not include broadcast news, there is no story segmentation task in the 2004 TDT Evaluation.
Samples
The images below are samples of the text data contained in this corpus.
