3 |
On Classifying whether Two Texts are on the Same Side of an Argument ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
AWESSOME : An unsupervised sentiment intensity scoring framework using neural word embeddings
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-domain Authorship Attribution and Style Change Detection
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Overview of PAN 2018. Author identification, author profiling, and author obfuscation
|
|
|
|
BASE
|
|
Show details
|
|
19 |
CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
|
|
Çöltekin, Çağrı; Kayadelen, Tolga; Droganova, Kira; Gokirmak, Memduh; Reddy, Siva; Kettnerová, Václava; Popel, Martin; Nitisaroj, Rattima; Leung, Herman; Pyysalo, Sampo; Ginter, Filip; Missilä, Anna; dePaiva, Valeria; Martínez Alonso, Héctor; Habash, Nizar; Banerjee, Esha; Tyers, Francis; Sanguinetti, Manuela; Lertpradit, Saran; Uszkoreit, Hans; Yu, Zhuoran; Li, Josie; Sulubacak, Umut; Simi, Maria; Harris, Kim; de Marneffe, Marie-Catherine; Burchardt, Aljoscha; Straka, Milan; Kanayama, Hiroshi; Rehm, Georg; Hlavacova, Jaroslava; Attia, Mohammed; Elkahky, Ali; Kwak, Sookyoung; Kanerva, Jenna; Nedoluzhko, Anna; Marheinecke, Katrin; Stella, Antonio; Lando, Tatiana; Badmaeva, Elena; Uresova, Zdenka; Hajic, Jan; Pitler, Emily; Potthast, Martin; Cinkova, Silvie; Ojala, Stina; Strnadová, Jana; Taji, Dima; Manning, Christopher D.; Mandl, Michael; Kirchner, Jesse; Mendonca, Gustavo; Alcalde, Hector Fernandez; Schuster, Sebastian; Petrov, Slav; Zeman, Daniel; Shimada, Atsuko; Nivre, Joakim; Luotolahti, Juhani; Hajic jr., Jan; Manurung, Ruli; Macketanz, Vivien. - : Association for Computational Linguistics, 2017. : country:USA, 2017. : place:Stroudsburg, PA, 2017
|
|
Abstract:
The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2017, one of two tasks was devoted to learning dependency parsers for a large number of languages, in a realworld setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe data preparation, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.
|
|
Keyword:
dependency syntax; evaluation; parsing; Universal Dependencies
|
|
URL: http://www.aclweb.org/anthology/K/K17/K17-3001.pdf https://doi.org/10.18653/v1/K17-3001 http://hdl.handle.net/2318/1652589
|
|
BASE
|
|
Hide details
|
|
20 |
Overview of PAN'17: Author Identification, Author Profiling, and Author Obfuscation
|
|
|
|
BASE
|
|
Show details
|
|
|
|