Task Proposal for SemEval-2014 - University of California.

SemEval-2010 Task 10: Linking Events and Their Participants in Discourse. The NAACL-HLT 2009 Workshop on Semantic Evaluations: Recent Achievements and Future Directions (SEW-09), Boulder, Colorado, USA, June 4, 2009. Data We annotate data of running text from the fiction domain. The training set is available here. The test set will be made.

SemEval-2016 Task 4 represents a sig-nicant departure from these previous editions. Al-though two of the subtasks (Subtasks A and B) are reincarnations of previous editions (SLMC classi-cation for Subtask A, binary classication for Sub-task B), SemEval-2016 Task 4 introduces two com-pletely new problems, taken individually (Subtasks.

Within the SemEval-2013 evaluation exercise, the TempEval-3 shared task aims to advance research on temporal information processing. It follows on from TempEval-1 and -2, with: a three-part struc-ture covering temporal expression, event, and tem-poral relation extraction; a larger dataset; and new singlemeasurestoranksystems ineachtaskandin.

Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text. While making such an assessment is trivial for humans, constructing algorithms and computational models that mimic human level performance represents a difficult and deep natural language understanding problem.

SemEval-2010 will be the 5th workshop on semantic evaluation. The first three workshops, Senseval-1 through Senseval-3, were focused on word sense disambiguation, each time growing in the number of languages offered in the tasks and in the number of participating teams.

Natural Language and Information Processing Research Group. 2019. Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. Ran Zmigrod, Sebastian J. Mielke, Hanna Wallach, Ryan Cotterell. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019. Active Learning for Financial Investment Reports. Sian Gooding and.

Also in 2013 there was a SemEval Shared Task on Student Response Analysis and one on Native Language Identification (hosted at the 2013 edition of this workshop). All of these competitions increased the visibility of the research space for NLP for building educational applications. While attendance has continued to be strong for several years.

The dataset is from task 1 in SemEval 2014. The distribution of data is shown in Table 3. The dataset is imbalanced, and the ratio among the contradiction, entailment, and neutral categories is roughly 1:2:4 not only in the training dataset but also in the trial and test datasets.

This page gives access to the data, evaluation script and official competition results for SemEval 2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers. For further details please see the official competition webpage.If you are interested, consider subscribing to the dedicated google group. Practice: 25 Sept 2017 to 7 Jan 2018.

Task: Essay Standards addressed: Describe the causes and effects of major events in America preceding the Declaration of Independence (e.g., the French and Indian War, Boston Massacre, Stamp Act) Explain the intent and significance of the Declaration of Independence Defend or criticize the justness of the Revolution Task: Some historians believe that the colonists were just, or right in how.

To train and test our semantic similarity system, we will use data from the SemEval-2015 Task 2 (Agirre et al., 2015), which also includes all data from similar tasks in 2012, 2013, and 2014. This dataset provides pairs of sentences together with a semantic similarity score between 0 and 5. A.

This paper presents the SemEval-2013 task on multilingual Word Sense Disambiguation. We describe our experience in producing a mul-tilingual sense-annotated corpus for the task. The corpus is tagged with BabelNet 1.1.1, a freely-available multilingual encyclopedic dictionary and, as a byproduct, WordNet 3.0 andtheWikipediasenseinventory.Wepresent.