Search Results for author:
Found 6 papers, 3 papers with code
The Past, Present, and Future of Typological Databases in NLP
We propose that such a view of typology has significant potential in the future, including in language modeling in low-resource scenarios.
CreoleVal: Multilingual Multitask Benchmarks for Creoles
Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research. While the genealogical ties between Creoles and a number of highly-resourced languages imply a significant potential for transfer learning, this potential is hampered due to this lack of annotated data.
Multilingual Gradient Word-Order Typology from Universal Dependencies
While information from the field of linguistic typology has the potential to improve performance on NLP tasks, reliable typological data is a prerequisite.
What is 'Typological Diversity' in NLP?
We recommend future work to include an operationalization of 'typological diversity' that empirically justifies the diversity of language samples.
RUG-1-Pegasussers at SemEval-2022 Task 3: Data Generation Methods to Improve Recognizing Appropriate Taxonomic Word Relations
This paper describes our system created for the SemEval 2022 Task 3: Presupposed Taxonomies - Evaluating Neural-network Semantics.
A Hybrid Rule-Based and Neural Coreference Resolution System with an Evaluation on Dutch Literature
We introduce a modular, hybrid coreference resolution system that extends a rule-based baseline with three neural classifiers for the subtasks mention detection, mention attributes (gender, animacy, number), and pronoun resolution.
