In this paper we present a description of the role of definitional verbal patterns for the extraction of semantic relations. Several studies show that semantic relations can be extracted from analytic definitions contained in machine-readable dictionaries (MRDs). In addition, definitions found in specialised texts are a good starting point to search for different types of definitions where other semantic relations occur. The extraction of definitional knowledge from specialised corpora represents another interesting approach for the extraction of semantic relations. Here, we present a descriptive analysis of definitional verbal patterns in Spanish and the first steps towards the development of a system for the automatic extraction of definitional knowledge.

Natural products, or specialized metabolites, are important for medicine and agriculture alike, as well as for the fitness of the organisms that produce them. Microbial genome mining aims at extracting metabolic information from genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process the likelihood of identifying truly novel biosynthetic systems is low. To overcome this limitation we previously introduced EvoMining, a genome mining approach that incorporates evolutionary principles.Here, we release and use our latest version of EvoMining, which includes novel visualization features and customizable databases, to analyze 42 central metabolic enzyme families conserved throughout Actinobacteria, Cyanobacteria, Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these enzyme families are lineage specific, opening a new metabolic space related to 'shell' enzymes, which have been overlooked to date. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving microbial adaptive evolution. By defining the origins and fates of metabolic enzymes, EvoMining not only complements traditional genome mining approaches as an unbiased and rule-independent strategy, but it opens the door to gain insights into the evolution of natural products biosynthesis. We anticipate that EvoMining will be broadly used for metabolic evolutionary studies, and to generate genome-mining predictions leading to unprecedented chemical scaffolds and new antibiotics. DATA SUMMARYDatabases have been deposited at Zenodo; DOI: 10.5281/zenodo.1162336 http://zenodo.org/deposit/1219709 Trees and metadata have been deposited in MicroReact GDH Actinobacteria https://microreact.org/project/r1IhjVm6X GDH Cyanobacteria https://microreact.org/project/HyjYUN7pQ) GDH Pseudomonas https://microreact.org/project/rJPC4EQa7 GDH Archaea https://microreact.org/project/ByUcvNmaX ALS Cyanobacteria https://microreact.org/project/B11HkUtdm EvoMining code has been deposited in gitHub https://github/nselem/evomining Docker container in Dockerhub https:// hub.docker.com/r/nselem/evomining/ We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

Resumen: En este trabajo se presenta un enfoque para la extracción automática de pares hipónimo-hiperónimo. En particular se propone un método de extracción de información léxica, orientado a la relación de hiponimia, que utiliza un conjunto de patrones léxicos propios del español, así como un esquema simétrico de calificación de pares/patrones cuyo objetivo es enriquecer la confiabilidad del método de extracción. La eficacia del método propuesto se evaluó obteniendo hipónimos correspondientes a un vocabulario de hiperónimos dado. Los resultados logrados confirman la utilidad del método propuesto para extraer hipónimos, así como la relevancia del esquema de calificación de pares/ patrones.Palabras Clave: Hipónimo, hiperónimo, patrones léxico-sintácticos, extracción de información. Hacia la identificación de relaciones dehiponimia/hiperonimia en Internet * (75) R. Ortega; C. Aguilar; L. Villaseñor; M. Montes y G. Sierra Towards the identification of hyponym/hypernym relations in the Internet 69Abstract: This paper presents an approach to the automatic extraction of hyponyms and hyperonyms. In particular, it proposes an information extraction method that is specially suited for identifying pairs of hyponym-hyperonym by using a set of Spanish lexical patterns. It also proposes a symmetric weighting scheme of pairs/patterns whose goal is to enhance the confidence of the extraction method. The effectiveness of the proposed approach was evaluated by extracting hyponyms from a given vocabulary of hyperonyms. Results show the usefulness of the proposed extraction method as well as the relevance of the pairs/patterns weighting scheme.

This chapter presents a critical review of the current state of natural language processing in Chile and Mexico. Specifically, a general review is made regarding the technological evolution of these countries in this area of research and development, as well as the progress they have made so far. Subsequently, the remaining problems and challenges are addressed. Specifically, two are analyzed in detail here: (1) the lack of a strategic policy that helps to establish stronger links between academia and industry and (2) the lack of a technological inclusion of the indigenous languages, which causes a deep digital divide between Spanish (considered in Chile and Mexico as their official language) with them.

We hope these articles may provide the reader with a wider scope for the current investigations that are being lead within the computational linguistics and natural language process fields as well as their implementation on current social and media problems. 

This article sketches the development of a method for mining concepts applied on medical corpora in Spanish. Such method is based in the approach formulated by Ananiadou and McNaught, who give a special relevance to the need to create and use natural language processing (NLP) tools, in order to extract information from large collections of documents, such as PubMed (www.ncbi.nlm.nih.gov/pubmed/). Thanks to this repository, projects such as the Corpus Genia (www.geniaproject.org), the MEDIE search engine (www.nactem.ac.uk/medie/), which considers syntactic criteria and semantics to extract medical concepts, or the Open Biological and Biomedical Ontology Project (http://obofoundry.org/), which focuses on the development of ontologies that provide an organized knowledge system in biomedicine. Particularly, this proposal focused in two objectives: (1) the extraction of specialized terms and (2) the identification of lexical-semantic relationships, in concrete hyponymy/hypernymy and meronymy.

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The automatic extraction of hyponymy-hypernymy relations in text corpus is one important task in Natural Language Processing. This chapter proposes a method for automatically extracting a set of hyponym-hyperonym pairs from a medical corpus in Spanish, expressed in analytical definitions. This kind of definition is composed by a term (the hyponym), a genus term (the hyperonym), and one or more differentiae, that is, a set of particular features proper to the defined term, e.g.: conjunctivitis is an infection of the conjunctiva of the eye. Definitions are obtained from definitional contexts, and then sequences of term and genus term. Then, the most frequent hyperonyms are used in order to filter relevant definitions. Additionally, using a bootstrapping technique, new hyponym candidates are extracted from the corpus, based on the previous set of hyponyms/hyperonyms detected.