VSP at PharmaCoNER 2019: Recognition of Pharmacological Substances, Compounds and Proteins with Recurrent Neural Networks in Spanish Clinical Cases

no code implementations • WS 2019 • V{\'\i}ctor Su{\'a}rez-Paniagua

The first layer uses the characters of each word and the resulting vector is aggregated to the second layer together with its word embedding in order to create the feature vector of the word.

named-entity-recognition Named Entity Recognition +2

UC3M-NII Team at SemEval-2018 Task 7: Semantic Relation Classification in Scientific Papers via Convolutional Neural Network

no code implementations • SEMEVAL 2018 • V{\'\i}ctor Su{\'a}rez-Paniagua, Isabel Segura-Bedmar, Akiko Aizawa

This paper reports our participation for SemEval-2018 Task 7 on extraction and classification of relationships between entities in scientific papers.

Clustering General Classification +4

LABDA at SemEval-2017 Task 10: Relation Classification between keyphrases via Convolutional Neural Network

no code implementations • SEMEVAL 2017 • V{\'\i}ctor Su{\'a}rez-Paniagua, Isabel Segura-Bedmar, Paloma Mart{\'\i}nez

In this paper, we describe our participation at the subtask of extraction of relationships between two identified keyphrases.

General Classification Lemmatization +3

Exploring Word Embedding for Drug Name Recognition

no code implementations • WS 2015 • Isabel Segura-Bedmar, V{\'\i}ctor Su{\'a}rez-Paniagua, Paloma Mart{\'\i}nez

Named Entity Recognition (NER) Relation Extraction +3