Learning about phraseology from corpora: A linguistically motivated approach for Multiword Expression identification.

Multiword Expressions (MWEs) are idiosyncratic combinations of words which pose important challenges to Natural Language Processing. Some kinds of MWEs, such as verbal ones, are particularly hard to identify in corpora, due to their high degree of morphosyntactic flexibility. This paper describes a linguistically motivated method to gather detailed information about verb+noun MWEs (VNMWEs) from corpora.

EUSKOR: End-to-end coreference resolution system for Basque.

This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristics of the language. The module has been integrated in a linguistic analysis pipeline obtaining an end-to-end coreference resolution system for the Basque language. The adaptation process explained can benefit and facilitate other languages with similar characteristics in the implementation of their coreference resolution systems.

Towards a top-down approach for an automatic discourse analysis for Basque: Segmentation and Central Unit detection tool.

Lately, discourse structure has received considerable attention due to the benefits its application offers in several NLP tasks such as opinion mining, summarization, question answering, text simplification, among others. When automatically analyzing texts, discourse parsers typically perform two different tasks: i) identification of basic discourse units (text segmentation) ii) linking discourse units by means of discourse relations, building structures such as trees or graphs. The resulting discourse structures are, in general terms, accurate at intra-sentence discourse-level relations, however they fail to capture the correct inter-sentence relations.

Interpretable deep learning to map diagnostic texts to ICD-10 codes.

Background: Automatic extraction of morbid disease or conditions contained in Death Certificates is a critical process, useful for billing, epidemiological studies and comparison across countries. The fact that these clinical documents are written in regular natural language makes the automatic coding process difficult because, often, spontaneous terms diverge strongly from standard reference terminology such as the International Classification of Diseases (ICD).

Objective: Our aim is to propose a general and multilingual approach to render Diagnostic Terms into the standard framework provided by the ICD.

Coreferential Relations in Basque: The Annotation Process.

In this paper we present the coreferential tagging of part of the EPEC Corpus of Basque. Although coreference is a pragmatic linguistic phenomenon highly dependent on the situational context, it shows some language-specific patterns that vary according to the features of each language. Due to the fact that Basque is not an Indo-European language, it differs considerably in grammar from the languages spoken in surrounding areas.

On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions.

The advances achieved in Natural Language Processing make it possible to automatically mine information from electronically created documents. Many Natural Language Processing methods that extract information from texts make use of annotated corpora, but these are scarce in the clinical domain due to legal and ethical issues. In this paper we present the creation of the IxaMed-GS gold standard composed of real electronic health records written in Spanish and manually annotated by experts in pharmacology and pharmacovigilance.