NameTag 2 is a named entity recognition tool. It recognizes named entities (e.g., names, locations, etc.) and can recognize both flat and embedded (nested) entities. NameTag 2 can be used either as a commandline tool or by requesting the NameTag webservice.
NameTag webservice can be found at:
https://lindat.mff.cuni.cz/services/nametag/
NameTag commandline tool can be downloaded from NameTag GitHub repository, branch nametag2:
git clone https://github.com/ufal/nametag -b nametag2
Latest models and documentation can be found at:
https://ufal.mff.cuni.cz/nametag/2
This software subject to the terms of the Mozilla Public License, v. 2.0 (http://mozilla.org/MPL/2.0/). The associated models are distributed under CC BY-NC-SA license.
Please cite as:
Jana Straková, Milan Straka, Jan Hajič (2019): Neural Architectures for Nested NER through Linearization. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5326-5331, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-950737-48-2 (https://aclweb.org/anthology/papers/P/P19/P19-1527/)
A simple way of browsing CoNLL format files in your terminal. Fast and text-based.
To open a CoNLL file, simply run: ./view_conll sample.conll
The output is piped through less, so you can use less commands to navigate the
file; by default the less searches for sentence beginnings, so you can use "n"
to go to next sentence and "N" to go to previous sentence. Close by "q". Trees
with a high number of non-projective edges may be difficult to read, as I have
not found a good way of displaying them intelligibly.
If you are on Windows and don't have less (but have Python), run like this: python view_conll.py sample.conll
For complete instructions, see the README file.
You need Python 2 to run the viewer.
Tokenizer, POS Tagger, Lemmatizer and Parser models for all 50 languages of Universal Depenencies 2.0 Treebanks, created solely using UD 2.0 data (http://hdl.handle.net/11234/1-1983). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/users-manual#universal_dependencies_20_models .
To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe .
In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.
Ministerstvo školství, mládeže a tělovýchovy České republiky@@CZ.02.1.01/0.0/0.0/16_013/0001781@@LINDAT/CLARIN - Výzkumná infrastruktura pro jazykové technologie - rozšíření repozitáře a výpočetní kapacity@@nationalFunds@@✖[remove]3