Automated Author ProfileVázquez, Gloria
Vázquez, Gloria
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: 1.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Introduction
SenSem (Sentence Semantics) Lexicons was developed by GRIAL, the Linguistic Applications Inter-University Research Group that includes the following Spanish institutions: the Universitat Autonoma de Barcelona, the Universitat de Barcelona, the Universitat de Lleida and the Universitat Oberta de Catalunya. It contains feature descriptions for approximately 1,300 Spanish verbs and 1,300 Catalan verbs in the SenSem Databank (LDC2015T02). GRIAL's work focuses on resources for applied linguistics, including lexicography, translation and natural language processing.
Data
The verb features for each language consist of two groups: those codified manually, including definition, WordNet synset, Aktionsart, arguments and semantic functions; and those extracted automatically from the SenSem Databank. Among the latter are verb frequency, semantic construction, syntactic categories and constituent order. The verbs analyzed correspond to the 250 most frequent verbs in Spanish and 320 lemmas in Catalan. Further information about the SenSem project can be obtained from the GRIAL website at http://grial.uab.es/sensem/corpus.
Data is presented in a single XML file per language.
Samples
Please view this sample.
Updates
None at this time.
Portions © 2015 Dr. Ana Fernandez Montraveta, Dr. Gloria Vázquez-Garcia, Trustees of the University of Pennsylvania
Authors
- Fernández, Ana ;
- Vázquez, Gloria
Introduction
SenSem (Sentence Semantics) Databank was developed by GRIAL, the Linguistic Applications Inter-University Research Group that includes the following Spanish institutions: the Universitat Autonoma de Barcelona, the Universitat de Barcelona, the Universitat de Lleida and the Universitat Oberta de Catalunya. It contains syntactic and semantic annotation for over 35,000 sentences, approximately one million words of Spanish and approximately 700,000 words of Catalan translated from the Spanish. GRIAL's work focuses on resources for applied linguistics, including lexicography, translation and natural language processing.
Each sentence in SenSem Databank was labeled according to the verb sense it exemplifies, the type of complement it takes (arguments or adjuncts) and the syntactic category and function. Each argument was also labeled with a semantic role. Further information about the SenSem project can be obtained from the GRIAL website at http://grial.uab.es/sensem/corpus.
Data
The Spanish source data includes texts from news journals (30,000 sentences) and novels (5,299 sentences). Those sentences represent around 1,000 different verb meanings that correspond to the 250 most frequent Spanish verbs. Verb frequencies were retrieved from a quantitative analysis of around 13 million words.
The Catalan corpus was developed by translating the news journal portion of the Spanish data set, resulting in a resource of over 700,000 sentences from which 391,267 sentences were annotated. Sentences were automatically translated and manually post-edited; some were re-annotated for sentence complements. Semantic information was the same for both languages. The Catalan sentences represent close to 1,300 different verbs.
Data is presented in a single XML file per language.
Samples
Please view this sample.
Updates
None at this time.
Portions © 2015 Dr. Ana Fernandez Montraveta, Dr. Gloria Vázquez-Garcia, Trustees of the University of Pennsylvania
Authors
- Fernández, Ana ;
- Vázquez, Gloria