Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Markus Eberts"'
Autor:
Markus Eberts, Adrian Ulges
Publikováno v:
EACL
We present a joint model for entity-level relation extraction from documents. In contrast to other approaches - which focus on local intra-sentence mention pairs and thus require annotations on mention level - our model operates on entity level. To d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e8c58afe7b962724863bf53c5e4678f
https://doi.org/10.18653/v1/2021.eacl-main.319
https://doi.org/10.18653/v1/2021.eacl-main.319
Publikováno v:
COLING
We introduce ManyEnt, a benchmark for entity typing models in few-shot scenarios. ManyEnt offers a rich typeset, with a fine-grain variant featuring 256 entity types and a coarse-grain one with 53 entity types. Both versions have been derived from th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22821170fbe4a1ad288cabe1e95147c6
https://doi.org/10.18653/v1/2020.coling-main.486
https://doi.org/10.18653/v1/2020.coling-main.486
Publikováno v:
ICMR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95656cee7fd33fcd04229d3af8a04117
https://doi.org/10.1145/3078971.3078994
https://doi.org/10.1145/3078971.3078994
Publikováno v:
ICDAR
We present AMIGO, an automatic indexer for video presentations which - given an e-lecture and supplementary slides - localizes the exact time and position of each slide displayed in the video footage. This offers richer access to viewers, including a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d09a1e12127909366d213ef37655392
https://doi.org/10.1109/icdar.2015.7333955
https://doi.org/10.1109/icdar.2015.7333955