Edition 1.1 of the PARSEME shared task on automatic identification of verbal multiword expressions
| Author | Affiliation | |
|---|---|---|
Ramisch, Carlos | ||
| Date |
|---|
2018 |
This paper describes the PARSEME Shared Task 1.1 on automatic identification of verbal multiword expressions. We present the annotation methodology, focusing on changes from last year’s shared task. Novel aspects include enhanced annotation guidelines, additional annotated data for most languages, corpora for some new languages, and new evaluation settings. Corpora were created for 20 languages, which are also briefly discussed. We report organizational principles behind the shared task and the evaluation metrics employed for ranking. The 17 participating systems, their methods and obtained results are also presented and analysed.
This work was supported by the IC1207 PARSEME COST action23, and national funded projects: LDPARSEME24 (LD14117) in the Czech Republic, and PARSEME-FR25 (ANR-14-CERA-0001) in France. Carla Parra Escartín is funded by the European Union’s Horizon 2020 programme under the Marie Skłodowska-Curie grant agreement No 713567, and Science Foundation Ireland in the ADAPT Centre (Grant 13/RC/2106) at Dublin City University. Behrang QasemiZadeh and Timm Lichte are funded by the Deutsche Forschungsgemeinschaft (DFG) within the CRC 991 “The Structure of Representations in Language, Cognition, and Science”. Veronika Vincze was supported by the UNKP-17-4 New National Excellence Program of the Ministry of Human Capacities, Hungary. The Slovenian team was supported by the Slovenian Research Agency via New grammar of contemporary standard Slovene: sources and methods (J6-8256 project). Ashwini Vaidya was supported by the DST-CSRI (Dept of Science and Technology, Govt. of India, Cognitive Science Research Initiative) fellowship. The Turkish team was supported by Bogaziçi University Research Fund Grant Number 14420