TDT5 Topics and Annotations
| Item Name: | TDT5 Topics and Annotations |
| Author(s): | Meghan Glenn, Stephanie Strassel, Junbo Kong, Kazuaki Maeda |
| LDC Catalog No.: | LDC2006T19 |
| ISBN: | 1-58563-418-2 |
| ISLRN: | 396-836-683-088-8 |
| DOI: | https://doi.org/10.35111/fjaq-y976 |
| Release Date: | December 19, 2006 |
| Member Year(s): | 2006 |
| DCMI Type(s): | Text |
| Data Source(s): | newswire |
| Application(s): | information detection, information extraction, language modeling, machine learning, machine translation, topic detection and tracking |
| Language(s): | English, Mandarin Chinese, Standard Arabic |
| Language ID(s): | eng, cmn, arb |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2006T19 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Glenn, Meghan, et al. TDT5 Topics and Annotations LDC2006T19. Web Download. Philadelphia: Linguistic Data Consortium, 2006. |
| Related Works: | View |
Introduction
TDT5 Topics and Annotations was developed by the Linguistic Data Consortium (LDC) and includes about 10,000 topic relevance judgments and other associated information for the TDT5 2004 evaluation topics.
This release contains complete relevance judgments, including the results of adjudication, in which discrepancies between system submissions and LDC annotations are reviewed and relevance judgments updated. This release also contains answer keys for the link detection task.
The TDT5 corpora were created by Linguistic Data Consortium with support from the DARPA TIDES (Translingual Information Detection, Extraction and Summarization) Program. The multilingual news text corresponding to this publication can be found in TDT5 Multilingual News Text (LDC2006T18).
Data
A total of 250 topics, numbered 55001 - 55250, were annotated by LDC using a search guided annotation technique. Details of the annotation process are described in the annotation task definition.
Approximately 25% of the topics are monolingual English (ENG), 25% are monolingual Mandarin Chinese (MAN), 25% are monolingual Arabic (ARB), and 25% are multilingual:
| 63 | ENG |
| 62 | MAN |
| 62 | ARB |
| 35 | ARB ENG MAN |
| 21 | ENG MAN |
| 7 | ARB ENG |
| 250 | total |
Broken down by language and counting both mono- and multi-lingual topics:
| 126 | ENG |
| 118 | MAN |
| 104 | ARB |
Samples
For an example of the data in this corpus, please review this sample (TXT) from the link detection files.
Updates
None at this time.