NER models for NameTag 2, named entity recognition tool, for English, German, Dutch, Spanish and Czech. Model documentation including performance can be found here: https://ufal.mff.cuni.cz/nametag/2/models . These models are for NameTag 2, named entity recognition tool, which can be found here: https://ufal.mff.cuni.cz/nametag/2 .
NER models for NameTag 2, named entity recognition tool, for English, German, Dutch, Spanish and Czech. Model documentation including performance can be found here: https://ufal.mff.cuni.cz/nametag/2/models . These models are for NameTag 2, named entity recognition tool, which can be found here: https://ufal.mff.cuni.cz/nametag/2 .
This is a trained model for the supervised machine learning tool NameTag 3 (https://ufal.mff.cuni.cz/nametag/3/), trained jointly on several NE corpora: English CoNLL-2003, German CoNLL-2003, Dutch CoNLL-2002, Spanish CoNLL-2002, Ukrainian Lang-uk, and Czech CNEC 2.0, all harmonized to flat NEs with 4 labels PER, ORG, LOC, and MISC. NameTag 3 is an open-source tool for both flat and nested named entity recognition (NER). NameTag 3 identifies proper names in text and classifies them into a set of predefined categories, such as names of persons, locations, organizations, etc. The model documentation can be found at https://ufal.mff.cuni.cz/nametag/3/models#multilingual-conll.
The NottDeuYTSch corpus contains over 33 million words taken from approximately 3 million YouTube comments from videos published between 2008 to 2018 targeted at a young, German-speaking demographic and represents an authentic language snapshot of young German speakers. The corpus was proportionally sampled based on video category and year from a database of 112 popular German-speaking YouTube channels in the DACH region for optimal representativeness and balance and contains a considerable amount of associated metadata for each comment that enable further longitudinal cross-sectional analyses.
The NottDeuYTSch corpus contains over 33 million words taken from approximately 3 million YouTube comments from videos published between 2008 to 2018 targeted at a young, German-speaking demographic and represents an authentic language snapshot of young German speakers. The corpus was proportionally sampled based on video category and year from a database of 112 popular German-speaking YouTube channels in the DACH region for optimal representativeness and balance and contains a considerable amount of associated metadata for each comment that enable further longitudinal cross-sectional analyses.
Segment consisting of footage showing objects from the scene of the assassination of acting Reich Protector Reinhard Heydrich, which was screened in all cinemas throughout the Protectorate. The camera shots capture a woman´s bicycle, a man´s coat, a cap with a visor, two leather briefcases, and a submachine gun made in England. The subtitles urge the members of the audience to identify the owners of the items in question and to help the police catch the perpetrators. The film was part of an aggressive campaign to spread fear of the annihilation of the nation, reinforced through the daily publication of the names of the executed in the media.