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It-Sr-NER tool is a CLARIN compatible NER web service for parallel texts with case study on Italian and Serbian; it can be used for recognizing and classifying named entities in bilingual natural language texts. Input parallel texts should be TMX (Translation Memory eXchange) files, e.g. Sr-It. It-Sr-NER can recognize six NER classes: demonyms (DEMO), works of art (WORK), person names (PERS), places (LOC), events (EVENT) and organisations (ORG). The service can also be used for monolingual text NER annotation for available spaCy NER models. It-Sr-NER uses a CNN architecture within the spaCy tool and Named Entity linking with Wikidata using spaCyOpenTapioca. For further details: API usage is described in: http://ners.jerteh.rs/4api A Postman example is available at https://github.com/rankastankovic/It-Sr-NER/blob/main/static/Postman_call_ners-mono.PNG

A Jupyter Notebook implementing a simple parser used to transform the Multilingual Data Stewardship terminology and Metadata, created in the Task 3.1 of the SSHOC project, into SKOS resources. The parser transforms the content in SKOS data following a set of mapping rules, the result is stored in two Turtle files.

Freeling IT is a web service that performs sentence splitting, tokenization, part-of-speech tagging, morphological analysis and lemmatization on Italian texts only. It was originally deployed within the EU-FP7-STREP PANACEA project (www.panacea-lr.eu) and implements the Freeling 2.1 libraries with no modification of the original code (which is available at http://devel.cpl.upc.edu/freeling/downloads?order=time&desc=1). For a description of the Freeling tool see Lluís Padró and Miquel Collado and Samuel Reese and Marina Lloberes and Irene Castellón. FreeLing 2.1: Five Years of Open-Source Language Processing Tools Proceedings of 7th Language Resources and Evaluation Conference (LREC 2010), ELRA La Valletta, Malta. May, 2010.

This is a lexical acquisition web-service for the automatic extraction of multiword expressions from large corpora. The service takes in input a POS-tagged corpus in CoNLL-X format plus a pair of POS-tags for the first and last word of a MWE, and outputs a list of extracted (candidate) multiword expressions with a set of linguistic and statistical information. The output can then be post-processed through filters that will refine and improve the accuracy of the extraction, and finally converted to an LMF-compliant XML lexical resource. The tool code is available open-source at https://github.com/francescafrontini/MWExtractor. Further details can be found in: Quochi Valeria & Frontini Francesca & Rubino Francesco. 2012. A MWE Acquisition and Lexicon Builder Web Service. In Proceedings of the 24th International Conference on Computational Linguistics (COLING 2012), December 10-14 2012, IIT Bombay, Mumbai, India. Frontini Francesca & Rubino Francesco & Quochi Valeria. 2012. Automatic Creation of quality multi-word Lexica from noisy text data. In Proceedings of the Sixth Workshop on Analytics for Noisy Unstructured Text Data (AND2012). December 9, 2012, IIT Bombay, Mumbai, India (Co-located with COLING2012).

The 'SCF Extractor (language independent)' is a service that performs inductive subcategorisation extraction from dependency parsed texts, formatted according to the CoNLL-X format. The SCF Extractor tool was developed at CNR-ILC and deployed as a soap web service within the EU-FP7-STREP PANACEA project (www.panacea-lr.eu). This version of the tool/service was not optimized for any language.; it requires 2 input data: 1) a dependency parsed text corpus the CONLL-X format; 2) a list of verb lemmas for which the subcategorization frames will be extracted.

Desr is a web service that performs dependency parsing on Italian tokenised, part-of-speech tagged, morphologically analysed texts. The web service was originally deployed by CNR-ILC within the EU-FP7-STREP PANACEA project (www.panacea-lr.eu) and implements the 2007 DeSR Parser [r4] code developed at the University of Pisa by Prof. Attardi and his group, and available at https://sourceforge.net/p/desr/code/HEAD/tree/branches. For details on the tool and code please see http://desr.sourceforge.net and the scientific references therein.

This is a LMF Lexical Multi level Merger web-service for the automatic merging of Lexical Entries, Syntactic Behaviours and Subcategorization Frames from two distinct LMF lexicons. The web-service takes two LMF lexicons, A and B, and a set of directives in input and outputs one or more LMF merged lexicon(s) according to different merging scenarios. Further details can be found in: Riccardo Del Gratta & Francesca Frontini & Monica Monachini &Valeria Quochi & Francesco Rubino& Matteo Abrate & Angelica Lo Duca. 2012. L-LEME: an Automatic Lexical Merger based on the LMF Standard. In Proceedings of the Workshop on Language Resource Merging (Colocated wiyh LREC 2012), May, 22 2012, Istanbul, Turkey

SCF Extractor (IT) is a service that performs inductive subcategorisation extraction from dependency parsed texts, formatted according to the CoNLL-X format. This tool/service was optimized for Italian. The SCF Extractor tool was developed at CNR-ILC and deployed as a soap web service within the EU-FP7-STREP PANACEA project (www.panacea-lr.eu). The service requires 2 input data: 1) a dependency parsed text corpus the CONLL-X format; 2) a list of verb lemmas for which the subcategorization frames will be extracted. For details on the tool design please see: - Rimell, Laura, Núria Bel, Muntsa Padró, Francesca Frontini, Monica Monachini and Valeria Quochi. 2012. D6.2 Integrated Final Version of the Components for Lexical Acquisition. Final Project Report. EC/FP7/248064. PANACEA project. - Caselli, Tommaso; Frontini, Francesca; Quochi, Valeria; Rubino, Francesco and Russo, Irene. (2012). Customizable SCF Acquisition in Italian.In Proceedings of LREC 2012, Istanbul, Turkey.