Automated Author ProfileUryupina, Olga
Uryupina, Olga
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.9 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Introduction
The ARRAU (Anaphora Resolution and Underspecification) Corpus of Anaphoric Information was developed by the University of Essex and the University of Trento. It contains annotations of multi-genre English texts for anaphoric relations with information about agreement and explicit representation of multiple antecedents for ambiguous anaphoric expressions and discourse antecedents for expressions which refer to abstract entities such as events, actions and plans.
The source texts in this release include task-oriented dialogues from the TRAINS-91 and TRAINS-93 corpora (the latter released through LDC, TRAINS Spoken Dialog Corpus LDC95S25), narratives from the English Pear Stories (a collection of narratives by subjects who watched a film and then recounted its contents), articles from the Wall Street Journal portions of the Penn Treebank (Treebank-2 LDC95T7) and the RST Discourse Treebank LDC2002T07, and the Vieira/Poesio Corpus which consists of training and test files from Treebank-2 and RST Discourse Treebank.
Data
The texts were annotated using the ARRAU guidelines which treat all noun phrases (NPs) as markables. Different semantic roles are recognized by distinguishing between referring expressions (that update or refer to a discourse model), and non-referring ones (including expletives, predicative expressions, quantifiers, and coordination). A variety of linguistic features were also annotated, including morphosyntactic agreement, grammatical function, semantic type (person, animate, concrete, action, time, other abstract) and genericity. The annotation was carried out using the MMAX2 annotation tool which allows text units to be marked at different levels.
The files in MMAX format have been organized so that they can be visualized using the MMAX2 tool or directly used as input/output for the BART toolkit which performs automatic coreference resolution including all necessary preprocessing steps.
Samples
Please view the following samplesL
Updates
None at this time.
Portions © 1987-1989 Dow Jones & Company, Inc., © 2001 Dr. Mary S. Erbaugh, © 2013 Massimo Poesio, © 1995, 1999, 2002, 2013 Trustees of the University of Pennsylvania
Authors
- Poesio, Massimo ;
- Artstein, Ron ;
- Uryupina, Olga ;
- Rodriguez, Kepa ;
- Delogu, Francesca ;
- Bristot, Antonella ;
- Hitzeman, Janet