The increasing flow of digital information requires the extraction, filtering and classification of
pertinent information from large volumes of texts. All these tasks greatly benefit from …

This paper describes a new advance in solving Cross-Lingual Question Answering (CL–QA)
tasks. It is built on three main pillars:(i) the use of several multilingual knowledge resources …

O HAREM, organizado pela Linguateca, representa a primeira avaliação conjunta de
sistemas de Reconhecimento de Entidades Mencionadas (REM) na língua portuguesa. Os …

This paper propose a model based on Named Entities Recognition, using Conditional
Random Fields (CRFs) for Spanish language. In this proposal different types of independent …

For our participation in GeoCLEF 2005 we have developed a system made up of three
modules. One of them is an Information Retrieval module and the others are Named Entity …

This paper presents a Named Entity Recognition (NER) system for Spanish which combines
the learning and knowledge approaches. Our contribution focuses on two matters: first, a …

English Named Entity Recognition (NER) is a main task into Natural Language Processing.
On the one hand, supporting the extraction of the information on unstructured data. On the …

En primer lugar, y no por seguir un orden de importancia, quiero agradecer a la Universidad
de Alicante por la oportunidad que me ha brindado de sentirme parte de esta maravillosa …

Extracción de Información es la llamada Named Entity Recognition (NER), que tiene por
objetivo la identificación de semánticas relevantes en un texto, y es necesaria por tanto para …

This paper presents a study on the impact and the need for Named Entity Recognition (NER)
in Cross–Lingual Question Answering (CL–QA) in order to overcome the errors that usually …