Jordi Turmo

Universitat Politecnica de Catalunya, Departament de Ciències de la Computació, Faculty Member

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Papers by Jordi Turmo

Links using a wide coverage semantic taxonomy

ABSTRACT

The TALP-UPC approach to Tweet-Norm 2013

Este artículo describe la metodología utilizada por el equipo TALP-UPC en la tarea propuesta en S... more Este artículo describe la metodología utilizada por el equipo TALP-UPC en la tarea propuesta en SEPLN 2013 para la normalización de tweets (Tweet-Norm). El sistema usa una batería de módulos para generar diferentes propuestas de corrección para cada palabra desconocida. La corrección definitiva se elige por votación ponderada según la precisión de cada módulo.

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Introducción a la tarea compartida Tweet-Norm 2013: Normalización léxica de tuits en espanol

An overview of the shared task is presented: description, corpora, annotation, preprocess, partic... more

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Language Technologies: Question Answering in Speech Transcripts

Computers in the Human Interaction Loop, 2009

The question answering (QA) task consists of providing short, relevant answers to natural languag... more

The TALP-QA System for Spanish at CLEF 2004: Structural and Hierarchical Relaxing of Semantic Constraints

Lecture Notes in Computer Science, 2005

Page 1. The TALP-QA System for Spanish at CLEF 2004: Structural and Hierarchical Relaxing of Sema... more

Overview of qast 2009-question answering on speech transcriptions

CLEF 2009 Workshop, 2009

Sibyl, a factoid question-answering system for spoken documents

ACM Transactions on Information Systems, 2012

In this article, we present a factoid question-answering system, Sibyl, specifically tailored for... more In this article, we present a factoid question-answering system, Sibyl, specifically tailored for question answering (QA) on spoken-word documents. This work explores, for the first time, which techniques can be robustly adapted from the usual QA on written documents to the more difficult spoken document scenario. More specifically, we study new information retrieval (IR) techniques designed or speech, and utilize several levels of linguistic information for the speech-based QA task. These include named-entity detection with phonetic information, syntactic parsing applied to speech transcripts, and the use of coreference resolution. Sibyl is largely based on supervised machine-learning techniques, with special focus on the answer extraction step, and makes little use of handcrafted knowledge. Consequently, it should be easily adaptable to other domains and languages. Sibyl and all its modules are extensively evaluated on the European Parliament Plenary Sessions English corpus, compa...

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KNOW2: tecnologías de comprensión del lenguaje para el acceso multilingüe a la información orientada a dominios

El objetivo de KNOW2 es avanzar en el desarrollo de un entorno integrado que permita la implantac... more El objetivo de KNOW2 es avanzar en el desarrollo de un entorno integrado que permita la implantación a bajo coste de portales verticales de acceso a la información para dominios concretos. El proyecto tiene una duración de tres años y acaba de comenzar en enero del 2010.The goal of the project is to explore integrated environments allowing the cost-effective deployment of vertical information access portals for speci c domains. The project started in January 2010, and will last three years

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UPC-CORE: What Can Machine Translation Evaluation Metrics and Wikipedia Do for Estimating Semantic Textual Similarity?

In this paper we discuss our participation to the 2013 Semeval Semantic Textual Similarity task. ... more In this paper we discuss our participation to the 2013 Semeval Semantic Textual Similarity task. Our core features include (i) a set of metrics borrowed from automatic machine translation, originally intended to evaluate automatic against reference translations and (ii) an instance of explicit semantic analysis, built upon opening paragraphs of Wikipedia 2010 articles. Our similarity estimator relies on a support vector regressor with RBF kernel. Our best approach required 13 machine translation metrics + explicit semantic analysis and ranked 65 in the competition. Our postcompetition analysis shows that the features have a good expression level, but overfitting and —mainly— normalization issues caused our correlation values to decrease.

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Hacia una clasificación verbal automática para el español: estudio sobre la relevancia de los diferentes tipos y configuraciones de información sintáctico-semántica

Linguamática, 2015

En este trabajo nos centramos en la adquisicion de clasificaciones verbales automaticas para el e... more En este trabajo nos centramos en la adquisicion de clasificaciones verbales automaticas para el espanol. Para ello realizamos una serie de experimentos con 20 sentidos verbales del corpus Sensem. Empleamos diferentes tipos de atributos que abarcan informacion linguistica diversa y un metodo de clustering jerarquico aglomerativo para generar varias clasificaciones. Comparamos cada una de estas clasificaciones automaticas con un gold standard creado semi-automaticamente teniendo en cuenta construcciones linguisticas propuestas desde la linguistica teorica. Esta comparacion nos permite saber que atributos son mas adecuados para crear de forma automatica una clasificacion coherente con la teoria sobre construcciones y cuales son las similitudes y diferencias entre la clasificacion verbal automatica y la que se basa en la teoria sobre construcciones linguisticas.

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PROcesamiento Semántico textual Avanzado para la detección de diagnósticos, procedimientos, otros conceptos y sus relaciones en informes MEDicos (PROSA-MED)

Proces. del Leng. Natural, 2017

El objetivo de este proyecto es desarrollar procesadores para el analisis automatico de textos me... more El objetivo de este proyecto es desarrollar procesadores para el analisis automatico de textos medicos, poniendo a disposicion de la comunidad cientifica y empresarial un conjunto amplio y versatil de herramientas y recursos linguisticos para el analisis morfologico, sintactico y semantico, asi como la asignacion de codigos diagnosticos y procedimientos a informes medicos segun el estandar CIE-10 y la deteccion de relaciones entre conceptos. Se desarrollaran herramientas para el espanol, dado su amplio uso en sistemas de salud a nivel internacional, explorando ademas otras lenguas con diferentes caracteristicas como el catalan y el vasco.

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Named entity recognition from spontaneous open-domain speech

Interspeech 2005, 2005

This paper presents an analysis of named entity recognition and classification in spontaneous spe... more This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promising results, approaching within 5% a system evaluated on clean textual data.

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Corpus Linguistics and Linguistic Theory, 2017

Similarity, which plays a key role in fields like cognitive science, psycholinguistics and natura... more Similarity, which plays a key role in fields like cognitive science, psycholinguistics and natural language processing, is a broad and multifaceted concept. In this work we analyse how two approaches that belong to different perspectives, the corpus view and the psycholinguistic view, articulate similarity between verb senses in Spanish. Specifically, we compare the similarity between verb senses based on their argument structure, which is captured through semantic roles, with their similarity defined by word associations. We address the question of whether verb argument structure, which reflects the expression of the events, and word associations, which are related to the speakers’ organization of the mental lexicon, shape similarity between verbs in a congruent manner, a topic which has not been explored previously. While we find significant correlations between verb sense similarities obtained from these two approaches, our findings also highlight some discrepancies between them ...

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Inductive Logic Programming and Its Application to the Temporal Expression Chunking Problem

TweetNorm: a benchmark for lexical normalization of Spanish tweets

Language Resources and Evaluation, 2015

TURBIO: A system for extracting information from restricted-domain texts

Lecture Notes in Computer Science, 1998

The more extended way of acquiring information for knowledge based systems is manually. However, ... more The more extended way of acquiring information for knowledge based systems is manually. However, the high cost of this approach and the availability of alternative Knowledge Sources has lead to an increasing use of automatic acquisition approaches. In this paper we present TURBIO, a Text-Based Intelligent System (TBIS) that extracts information contained in restricted-domain documents. The system acquires part of its knowledge about the structure of the documents and the way the information is presented (i.e. syntactic-semantic rules) from a training set of them. Then, a database is created by means of applying these syntactic-semantic rules to extract the information contained in the whole documents.

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Selecting a Relevant Set of Examples to Learn IE-Rules

Lecture Notes in Computer Science, 2001

The growing availability of online text has lead to an increase in the use of automatic knowledge... more The growing availability of online text has lead to an increase in the use of automatic knowledge acquisition approaches from textual data, as in Information Extraction (IE). Some IE systems use knowledge learned by single-concept learning systems, as sets of IE rules. Most of such systems need both sets of positive and negative examples. However, the manual selection of positive examples can be a very hard task for experts, while automatic methods for selecting negative examples can generate extremely large example sets, in spite of the fact that only a small subset of them is relevant to learn. This paper brie y describes a more portable multi-concept learning system and presents a methodology to select a relevant set of training examples.

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A hybrid unsupervised approach for document clustering

Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, 2005

We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clust... more We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to automatically select a subset of the clusters generated by the first algorithm as the initial points of the second one. Furthermore, our initialization algorithm generates not only an initial model for the iterative refinement algorithm but also an estimate of the model dimension, thus eliminating another important element of human supervision. We have evaluated the proposed system on five real-world document collections. The results show that our approach generates clustering solutions of higher quality than both its individual components.

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Robust Question Answering for Speech Transcripts: UPC Experience in QAst 2008

Lecture Notes in Computer Science, 2009

This paper describes the participation of the Technical University of Catalonia in the CLEF 2009 ... more This paper describes the participation of the Technical University of Catalonia in the CLEF 2009 Question Answering on Speech Transcripts track. We have participated in the English and Spanish scenarios of QAst. For both manual and automatic transcripts we have used a robust factual Question Answering that uses minimal syntactic information. We have also developed a NERC designed to handle automatic transcripts. We perform a detailed analysis of our results and draw conclusions relating QA performance to word error rate and the difference between written and spoken questions.

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An analysis of bootstrapping for the recognition of temporal expressions

Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing - SemiSupLearn '09, 2009

We present a semi-supervised (bootstrapping) approach to the extraction of time expression mentio... more We present a semi-supervised (bootstrapping) approach to the extraction of time expression mentions in large unlabelled corpora. Because the only supervision is in the form of seed examples, it becomes necessary to resort to heuristics to rank and filter out spurious patterns and candidate time expressions. The application of bootstrapping to time expression recognition is, to the best of our knowledge, novel. In this paper, we describe one such architecture for bootstrapping Information Extraction (IE) patterns-suited to the extraction of entities, as opposed to events or relations-and summarize our experimental findings. These point out to the fact that a pattern set with a good increase in recall with respect to the seeds is achievable within our framework while, on the other side, the decrease in precision in successive iterations is succesfully controlled through the use of ranking and selection heuristics. Experiments are still underway to achieve the best use of these heuristics and other parameters of the bootstrapping algorithm.

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