This WS creates an alignment file combining the Hunalign output and two sentences id lists extracted from GrAF documents.
Provider:
Universitat Pompeu Fabra (UPF)
This WS creates a compress file (in TGZ format) with output documents stored on this same server using their URL
Provider:
Universitat Pompeu Fabra (UPF)
This WS is based on the Twitter NLP tool developed by Noah's ARK group (Noah Smith's research group at the Language Technologies Institute, School of Computer Science, Carnegie Mellon University). A fast and robust Java-based tokenizer and part-of-speech tagger for Twitter, its training data of manually labeled POS annotated tweets, a web-based annotation tool, and hierarchical word clusters from unlabeled tweets. The language supported is English.
Provider:
Universitat Pompeu Fabra (UPF)
This WS randomizes the order of the translation units in TMX files. The goal is to make it difficult to reproduce the original text. The input size limit is 100 MB. Language independent WS.
Provider:
Universitat Pompeu Fabra (UPF)
This WS will scramble the lines in a parallel text corpus keeping the alignment. The goal is to make it difficult to reproduce the original text. The input size limit is 100 MB. Language independent WS.
Provider:
Universitat Pompeu Fabra (UPF)
This WS scrambles the lines in a file. The goal is to make it difficult to reproduce the original text. The input size limit is 100 MB. Language independent WS.
Provider:
Universitat Pompeu Fabra (UPF)
This WS collects all the headers of input XML files used in a Taverna workflow. The metadata that can be stored in the resulting XML file are: 1) workflow name, 2) workflow myExperiment link, 3) processors list, and 4) list of XML headers.
Provider:
Universitat Pompeu Fabra (UPF)
This WS substitutes proper nouns with tags. This process anonymizes an input text by eliminating any person, place, corporation, etc. name. The service automatically calls the FreeLing WS and makes use of its Named Entity Recognition tool to detect proper nouns. The languages supported are English, Catalan, Spanish, Asturian, Welsh, Galician, Italian, Russian and Portuguese.
Provider:
Universitat Pompeu Fabra (UPF)
This WS calls an instance of MaltParser for Spanish trained with the IULA treebank developed in the Metanet4you project. The input of this WS is plain text. The service performs PoS tagging with FreeLing and then performs the dependency parsing using Malt parser. The output follows CoNLL format.
Provider:
Universitat Pompeu Fabra (UPF)
Given a LMF file with nouns classified with a score (see Nouns classifier Web Services), this WS filters the nouns with confidence over a desired threshold. Language independent WS.
Provider:
Universitat Pompeu Fabra (UPF)
Given two LMF files, this webservice merges them into a single LMF file. It works for LMF files encoding the information in the same way, i.e. same labels, values and structure. This will work, for example, for merging different lexica learnt under PANACEA platform. If the LMF files contain equivalent information encoded in different ways, a mapping into a common format should be previously performed.
WARNING: this version of the webservice only works for LMF files without references. Thi...
Provider:
Universitat Pompeu Fabra (UPF)
This WS identifies location nouns in a part of speech tagged text (with FreeLing Morphosyntactic tagger V 3.0 WS). The classification is performed with a pre-trained Decision Tree. The output is a LMF file with the classifier prediction for each noun. You can choose to have this prediction as:
- "scored": each noun gets a score of being or not being a member of the class (bigger than 0 means class member, smaller, non member of the class)
- "filtered": the nouns are filtered according to t...
Provider:
Universitat Pompeu Fabra (UPF)
This WS identifies human nouns in a part of speech tagged text (with FreeLing Morphosyntactic tagger V 3.0 WS). The classification is performed with a pre-trained Decision Tree. The ouptut is a LMF file with the classifier prediction for each noun. ou can choose to have this prediction as:
- "scored": each noun gets a score of being or not being a member of the class (bigger than 0 means class member, smaller, non member of the class)
- "filtered": the nouns are filtered according to their ...
Provider:
Universitat Pompeu Fabra (UPF)
This WS performs a FreeLing-based chunker parser (v 3.0). The WS requires a plain text input. The possible outputs formats are FreeLing , XML, and XML CQP ready. The languages supported are English, Catalan, Spanish, Asturian and Galician.
Provider:
Universitat Pompeu Fabra (UPF)
This WS deploys a FreeLing-based dependency parser (v 3.0). The WS requires a plain text input. The possible outputs formats are FreeLing, XML, and XML CQP ready. The languages supported are English, Catalan, Spanish, Asturian and Galician.
Provider:
Universitat Pompeu Fabra (UPF)
This WS performs a FreeLing-based sentence splitter (v 3.0). The WS splits a file in plain text format and UTF-8 encoded into units (tokens). Output sentences are separated by empty lines. The languages supported are English, Catalan, Spanish, Asturian, Welsh, Galician, Italian, Russian and Portuguese.
Provider:
Universitat Pompeu Fabra (UPF)
This WS deploys a FreeLing-based text tokenizer (v 3.0). The WS splits a file in plain text format and UTF-8 encoded into units (tokens). The languages supported are Catalan, English, Galician, Italian, Portuguese, Russian, Spanish, Welsh, and Asturian.
Provider:
Universitat Pompeu Fabra (UPF)
This WS performs a FreeLing-based part-of-speech tagger (v 3.0). WS job duration depends on the server load, approximately 1 million words takes one minute. The languages supported are English, Catalan, Spanish, Asturian, Welsh, Galician, Italian, and Portuguese.
Provider:
Universitat Pompeu Fabra (UPF)
This Web Service deploys a FreeLing-based morphological analyzer (v 3.0). The languages supported are English, Catalan, Spanish, Asturian, Welsh, Galician, Italian, Russian and Portuguese.
Provider:
Universitat Pompeu Fabra (UPF)
Given a XML signatures file (signatures.xml) and the indicators file (indicators.txt) with the nouns that belong or not to the class, this WS creates a file in ARFF format to experiment with Weka. Warning: the default encoding for input and outputs files is ISO-8859-1. It may be changed using optional parameters, but the two input files must have the same encoding, which must be indicated in the headers of the XML file.
Provider:
Universitat Pompeu Fabra (UPF)
Marc Poch Riera
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