1 |
FiNER-139: A Financial Numeric Entity Recognition Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
FiNER-139: A Financial Numeric Entity Recognition Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
MultiEURLEX -- A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collections ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
SemEval-2021 Task 5: Toxic Spans Detection ...
|
|
|
|
Abstract:
The Toxic Spans Detection task of SemEval-2021 required participants to predict the spans of toxic posts that were responsible for the toxic label of the posts. The task could be addressed as supervised sequence labeling, using training data with gold toxic spans provided by the organisers. It could also be treated as rationale extraction, using classifiers trained on potentially larger external datasets of posts manually annotated as toxic or not, without toxic span annotations. For the supervised sequence labeling approach and evaluation purposes, posts previously labeled as toxic were crowd-annotated for toxic spans. Participants submitted their predicted spans for a held-out test set, and were scored using character-based F1. This overview summarises the work of the 36 teams that provided system descriptions. ...
|
|
URL: https://dx.doi.org/10.48448/r5k8-kf50 https://underline.io/lecture/30019-semeval-2021-task-5-toxic-spans-detection
|
|
BASE
|
|
Hide details
|
|
11 |
MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Machine Extraction of Tax Laws from Legislative Texts
|
|
|
|
In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021)
|
|
BASE
|
|
Show details
|
|
13 |
Deception detection in text and its relation to the cultural dimension of individualism/collectivism ...
|
|
|
|
BASE
|
|
Show details
|
|
16 |
Extracting Linguistic Resources from the Web for Concept-to-Text Generation ...
|
|
|
|
BASE
|
|
Show details
|
|
17 |
An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
|
|
|
|
In: ISSN: 1471-2105 ; BMC Bioinformatics ; https://hal.sorbonne-universite.fr/hal-01156600 ; BMC Bioinformatics, BioMed Central, 2015, 16 (1), pp.138. ⟨10.1186/s12859-015-0564-6⟩ (2015)
|
|
BASE
|
|
Show details
|
|
18 |
Generating Natural Language Descriptions from OWL Ontologies: the NaturalOWL System ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|