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172. MSTperl parser
- Creator:
- Rosa, Rudolf
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- toolService and tool
- Subject:
- parser, NLP, Treex, parsing, and dependency
- Language:
- Czech and English
- Description:
- MSTperl is a Perl reimplementation of the MST parser of Ryan McDonald (http://www.seas.upenn.edu/~strctlrn/MSTParser/MSTParser.html). MST parser (Maximum Spanning Tree parser) is a state-of-the-art natural language dependency parser -- a tool that takes a sentence and returns its dependency tree. In MSTperl, only some functionality was implemented; the limitations include the following: the parser is a non-projective one, curently with no possibility of enforcing the requirement of projectivity of the parse trees; only first-order features are supported, i.e. no second-order or third-order features are possible; the implementation of MIRA is that of a single-best MIRA, with a closed-form update instead of using quadratic programming. On the other hand, the parser supports several advanced features: parallel features, i.e. enriching the parser input with word-aligned sentence in other language; adding large-scale information, i.e. the feature set enriched with features corresponding to pointwise mutual information of word pairs in a large corpus (CzEng). The MSTperl parser is tuned for parsing Czech. Trained models are available for Czech, English and German. We can train the parser for other languages on demand, or you can train it yourself -- the guidelines are part of the documentation. The parser, together with detailed documentation, is avalable on CPAN (http://search.cpan.org/~rur/Treex-Parser-MSTperl/). and The research has been supported by the EU Seventh Framework Programme under grant agreement 247762 (Faust), and by the grants GAUK116310 and GA201/09/H057.
- Rights:
- Artistic License 2.0, http://opensource.org/licenses/Artistic-2.0, and PUB
173. MSTperl parser (2015-05-19)
- Creator:
- Rosa, Rudolf
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- toolService and tool
- Subject:
- parser, NLP, Treex, parsing, and dependency
- Language:
- Czech and English
- Description:
- MSTperl is a Perl reimplementation of the MST parser of Ryan McDonald (http://www.seas.upenn.edu/~strctlrn/MSTParser/MSTParser.html). MST parser (Maximum Spanning Tree parser) is a state-of-the-art natural language dependency parser -- a tool that takes a sentence and returns its dependency tree. In MSTperl, only some functionality was implemented; the limitations include the following: the parser is a non-projective one, curently with no possibility of enforcing the requirement of projectivity of the parse trees; only first-order features are supported, i.e. no second-order or third-order features are possible; the implementation of MIRA is that of a single-best MIRA, with a closed-form update instead of using quadratic programming. On the other hand, the parser supports several advanced features: parallel features, i.e. enriching the parser input with word-aligned sentence in other language; adding large-scale information, i.e. the feature set enriched with features corresponding to pointwise mutual information of word pairs in a large corpus (CzEng); weighted/unweighted parser model interpolation; combination of several instances of the MSTperl parser (through MST algorithm); combination of several existing parses from any parsers (through MST algorithm). The MSTperl parser is tuned for parsing Czech. Trained models are available for Czech, English and German. We can train the parser for other languages on demand, or you can train it yourself -- the guidelines are part of the documentation. The parser, together with detailed documentation, is avalable on CPAN (http://search.cpan.org/~rur/Treex-Parser-MSTperl/). and The research has been supported by the EU Seventh Framework Programme under grant agreement 247762 (Faust), and by the grants GAUK116310 and GA201/09/H057.
- Rights:
- Artistic License 2.0, http://opensource.org/licenses/Artistic-2.0, and PUB
174. MTMonkey
- Creator:
- Tamchyna, Aleš, Dušek, Ondřej, and Rosa, Rudolf
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- toolService and infrastructure
- Subject:
- machine translation, distributed computing, web service, and infrastructure
- Description:
- MTMonkey is a web service which handles and distributes JSON-encoded HTTP requests for machine translation (MT) among multiple machines running an MT system, including text pre- and post processing. It consists of an application server and remote workers which handle text processing and communicate translation requests to MT systems. The communication between the application server and the workers is based on the XML-RPC protocol. and The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 257528 (KHRESMOI). This work has been using language resources developed and/or stored and/or distributed by the LINDAT-Clarin project of the Ministry of Education of the Czech Republic (project LM2010013). This work has been supported by the AMALACH grant (DF12P01OVV02) of the Ministry of Culture of the Czech Republic.
- Rights:
- Apache License 2.0, http://opensource.org/licenses/Apache-2.0, and PUB
175. MUSCIMarker
- Creator:
- Hajič, Jan Jr
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- tool and toolService
- Subject:
- image annotation, Python, and music notation
- Description:
- MUSCIMarker is an open-source tool for annotating visual objects and their relationships in binary images. It is implemented in Python, known to run on Windows, Linux and OS X, and supports working offline. MUSCIMarker is being used for creating a dataset of musical notation symbols, but can support any object set. The user documentation online is currently (12.2016) incomplete, as it is continually changing to reflect annotators' comments and incorporate new features. This version of the software is *not* the final one, and it is under continuous development (we're currently working on adding grayscale image support with auto-binarization, and Android support for touch-based annotation). However, the current version (1.1) has already been used to annotate more than 100 pages of sheet music, over all the major desktop OSes, and I believe it is already in a state where it can be useful beyond my immediate music notation data gathering use case.
- Rights:
- Apache License 2.0, http://opensource.org/licenses/Apache-2.0, and PUB
176. NameTag
- Creator:
- Straka, Milan and Straková, Jana
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- toolService and tool
- Subject:
- named entity recognizer
- Language:
- English
- Description:
- NameTag is an open-source tool for named entity recognition (NER). NameTag identifies proper names in text and classifies them into predefined categories, such as names of persons, locations, organizations, etc. NameTag is distributed as a standalone tool or a library, along with trained linguistic models. In the Czech language, NameTag achieves state-of-the-art performance (Straková et al. 2013). NameTag is a free software under LGPL license and the linguistic models are free for non-commercial use and distributed under CC BY-NC-SA license, although for some models the original data used to create the model may impose additional licensing conditions.
- Rights:
- Not specified
177. NameTag 2
- Creator:
- Straková, Jana
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- tool and toolService
- Subject:
- named entity recognition and named entity recognizer
- Description:
- 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/)
- Rights:
- Mozilla Public License 2.0, http://opensource.org/licenses/MPL-2.0, and PUB
178. NameTag service description
- Creator:
- Straková, Jana and Straka, Milan
- Publisher:
- Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
- Type:
- service and toolService
- Subject:
- named entity recognition, NameTag, and WeblichtXML
- Language:
- Czech, German, English, Spanish, and Dutch
- Description:
- Metadata description of nametag (http://hdl.handle.net/11234/1-3633, https://lindat.mff.cuni.cz/services/nametag/) provided for weblicht.
- Rights:
- Not specified
179. Natural Language Toolkit
- Type:
- toolService
- Description:
- Open source Python modules, linguistic data and documentation for research and development in natural language processing, supporting dozens of NLP tasks. NLTK includes the following software modules (~120k lines of Python code): Corpus readers interfaces to many corpora Tokenizers whitespace, newline, blankline, word, treebank, sexpr, regexp, Punkt sentence segmenter Stemmers Porter, Lancaster, regexp Taggers regexp, n-gram, backoff, Brill, HMM, TnT Chunkers regexp, n-gram, named-entity Parsers recursive descent, shift-reduce, chart, feature-based, probabilistic, dependency, ... Semantic interpretation untyped lambda calculus, first-order models, DRT, glue semantics, hole semantics, parser interface WordNet WordNet interface, lexical relations, similarity, interactive browser Classifiers decision tree, maximum entropy, naive Bayes, Weka interface, megam Clusterers expectation maximization, agglomerative, k-means Metrics accuracy, precision, recall, windowdiff, distance metrics, inter-annotator agreement coefficients, word association measures, rank correlation Estimation uniform, maximum likelihood, Lidstone, Laplace, expected likelihood, heldout, cross-validation, Good-Turing, Witten-Bell Miscellaneous unification, chatbots, many utilities NLTK-Contrib (less mature) categorial grammar (Lambek, CCG), finite-state automata, hadoop (MapReduce), kimmo, readability, textual entailment, timex, TnT interface, inter-annotator agreement
- Rights:
- Not specified
180. Nederlandse Familienamen Databank (Dutch Database of Family Names)
- Publisher:
- Meertens Institute KNAW The Netherlands
- Format:
- application/octet-stream
- Type:
- toolService
- Language:
- Dutch
- Description:
- Enriched database of (mainly) Dutch family names, based on 1947 census (in progress; currently 90.000 entries from 140.000 max)
- Rights:
- Meertens Institute KNAW The Netherlands