The `corpipe24-corefud1.2-240906` is a `mT5-large`-based multilingual model for coreference resolution usable in CorPipe 24 (https://github.com/ufal/crac2024-corpipe). It is released under the CC BY-NC-SA 4.0 license.
The model is language agnostic (no corpus id on input), so it can be in theory used to predict coreference in any `mT5` language.
This model jointly predicts also the empty nodes needed for zero coreference. The paper introducing this model also presents an alternative two-stage approach first predicting empty nodes (via https://www.kaggle.com/models/ufal-mff/crac2024_zero_nodes_baseline/) and then performing coreference resolution (via http://hdl.handle.net/11234/1-5673), which is circa twice as slow but slightly better.
Corpus of texts in 12 languages. For each language, we provide one training, one development and one testing set acquired from Wikipedia articles. Moreover, each language dataset contains (substantially larger) training set collected from (general) Web texts. All sets, except for Wikipedia and Web training sets that can contain similar sentences, are disjoint. Data are segmented into sentences which are further word tokenized.
All data in the corpus contain diacritics. To strip diacritics from them, use Python script diacritization_stripping.py contained within attached stripping_diacritics.zip. This script has two modes. We generally recommend using method called uninames, which for some languages behaves better.
The code for training recurrent neural-network based model for diacritics restoration is located at https://github.com/arahusky/diacritics_restoration.
This bilingual thesaurus (French-English), developed at Inist-CNRS, covers the concepts from the emerging COVID-19 outbreak which reminds the past SARS coronavirus outbreak and Middle East coronavirus outbreak. This thesaurus is based on the vocabulary used in scientific publications for SARS-CoV-2 and other coronaviruses, like SARS-CoV and MERS-CoV. It provides a support to explore the coronavirus infectious diseases. The thesaurus can be browsed and queried by humans and machines on the Loterre portal (https://www.loterre.fr), via an API and an rdf triplestore. It is also downloadable in PDF, SKOS, csv and json-ld formats. The thesaurus is made available under a CC-by 4.0 license.