English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts

MPS-Authors
/persons/resource/persons180796

Chu,  Cuong Xuan
Databases and Information Systems, MPI for Informatics, Max Planck Society;

/persons/resource/persons212613

Razniewski,  Simon
Databases and Information Systems, MPI for Informatics, Max Planck Society;

/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

External Resource
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Chu, C. X., Razniewski, S., & Weikum, G. (2020). ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts. In Q. Liu, & D. Schlangen (Eds.), The 2020 Conference on Empirical Methods in Natural Language Processing (pp. 100-106). Stroudsburg, PA: ACM. doi:10.18653/v1/2020.emnlp-demos.14.


Cite as: http://hdl.handle.net/21.11116/0000-0007-EED5-D
Abstract
There is no abstract available