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Recognising and interpreting named temporal expressions
- In RANLP
, 2013
"... Abstract This paper introduces a new class of temporal expression -named temporal expressions -and methods for recognising and interpreting its members. The commonest temporal expressions typically contain date and time words, like April or hours. Research into recognising and interpreting these ty ..."
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Abstract This paper introduces a new class of temporal expression -named temporal expressions -and methods for recognising and interpreting its members. The commonest temporal expressions typically contain date and time words, like April or hours. Research into recognising and interpreting these typical expressions is mature in many languages. However, there is a class of expressions that are less typical, very varied, and difficult to automatically interpret. These indicate dates and times, but are harder to detect because they often do not contain time words and are not used frequently enough to appear in conventional temporally-annotated corporafor example Michaelmas or Vasant Panchami. Using Wikipedia and linked data, we automatically construct a resource of English named temporal expressions, and use it to extract training examples from a large corpus. These examples are then used to train and evaluate a named temporal expression recogniser. We also introduce and evaluate rules for automatically interpreting these expressions, and we observe that use of the rules improves temporal annotation performance over existing corpora.
The uComp Protége ́ Plugin: Crowdsourcing Enabled Ontology Engineering
"... Abstract. Crowdsourcing techniques have been shown to provide ef-fective means for solving a variety of ontology engineering problems. Yet, they are mainly being used as external means to ontology engi-neering, without being closely integrated into the work of ontology engi-neers. In this paper we i ..."
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Abstract. Crowdsourcing techniques have been shown to provide ef-fective means for solving a variety of ontology engineering problems. Yet, they are mainly being used as external means to ontology engi-neering, without being closely integrated into the work of ontology engi-neers. In this paper we investigate how to closely integrate crowdsourcing into ontology engineering practices. Firstly, we show that a set of basic crowdsourcing tasks are used recurrently to solve a range of ontology engineering problems. Secondly, we present the uComp Protége ́ plugin that facilitates the integration of such typical crowdsourcing tasks into ontology engineering work from within the Protége ́ ontology editing en-vironment. An evaluation of the plugin in a typical ontology engineering scenario where ontologies are built from automatically learned semantic structures, shows that its use reduces the working times for the ontol-ogy engineers 11 times, lowers the overall task costs with 40 % to 83% depending on the crowdsourcing settings used and leads to data quality comparable with that of tasks performed by ontology engineers.
Information Needs and Behaviors of User Groups Issues and Non-Issues in Professional Search
"... This position paper points out some false contrasts which are made between Boolean and ranked retrieval, and also between the use in search of statistical machine learning and explicit knowledge representations. Some directions for future research are pointed out. 1. ..."
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This position paper points out some false contrasts which are made between Boolean and ranked retrieval, and also between the use in search of statistical machine learning and explicit knowledge representations. Some directions for future research are pointed out. 1.
uni-wuerzburg.de
, 2013
"... Acknowledgments. This work was partly funded by Deutsche Forschungsgemeinschaft (DFG) under grants HO 4770/1-1 and TR257/31-1, and the COST QUALINET Action IC1003. The authors alone ..."
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Acknowledgments. This work was partly funded by Deutsche Forschungsgemeinschaft (DFG) under grants HO 4770/1-1 and TR257/31-1, and the COST QUALINET Action IC1003. The authors alone
Crowd-based Ontology Engineering with the uComp Protége ́ Plugin
"... Abstract. Crowdsourcing techniques have been shown to provide ef-fective means for solving a variety of ontology engineering problems. Yet, they are mainly being used as external means to ontology engi-neering, without being closely integrated into the work of ontology engi-neers. In this paper we i ..."
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Abstract. Crowdsourcing techniques have been shown to provide ef-fective means for solving a variety of ontology engineering problems. Yet, they are mainly being used as external means to ontology engi-neering, without being closely integrated into the work of ontology engi-neers. In this paper we investigate how to closely integrate crowdsourcing into ontology engineering practices. Firstly, we show that a set of basic crowdsourcing tasks are used recurrently to solve a range of ontology engineering problems. Secondly, we present the uComp Protége ́ plugin that facilitates the integration of such typical crowdsourcing tasks into ontology engineering work from within the Protége ́ ontology editing en-vironment. An evaluation of the plugin in a typical ontology engineering scenario where ontologies are built from automatically learned semantic structures, shows that its use reduces the working times for the ontology engineers 11 times, lowers the overall task costs with 40 % to 83 % depend-ing on the crowdsourcing settings used and leads to data quality com-parable with that of tasks performed by ontology engineers. Evaluations on a large ontology from the anatomy domain confirm that crowdsourc-ing is a scalable and effective method: good quality results (accuracy of 89 % and 99%) are obtained while achieving cost reductions with 75% from the ontology engineer costs and providing comparable overall task duration.
Analysis of Named Entity Recognition and Linking for Tweets
"... Applying natural language processing for mining and intelligent information ac-cess to tweets (a form of microblog) is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-depen ..."
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Applying natural language processing for mining and intelligent information ac-cess to tweets (a form of microblog) is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-dependent, and dynamic nature. Information extraction from tweets is typically performed in a pipeline, comprising consecutive stages of language identification, tokenisation, part-of-speech tagging, named entity recognition and entity disambiguation (e.g. with respect to DBpedia). In this work, we describe a new Twitter entity disam-biguation dataset, and conduct an empirical analysis of named entity recognition and disambiguation, investigating how robust a number of state-of-the-art sys-tems are on such noisy texts, what the main sources of error are, and which problems should be further investigated to improve the state of the art.
Sentence diagrams: their evaluation and combination
"... {hana,hladka,luksova} (at) ufal.mff.cuni.cz The purpose of our work is to explore the possibility of using sentence diagrams produced by schoolchildren as training data for automatic syntactic analysis. We have implemented a sentence diagram editor that schoolchildren can use to practice morphology ..."
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{hana,hladka,luksova} (at) ufal.mff.cuni.cz The purpose of our work is to explore the possibility of using sentence diagrams produced by schoolchildren as training data for automatic syntactic analysis. We have implemented a sentence diagram editor that schoolchildren can use to practice morphology and syntax. We collect their diagrams, combine them into a single diagram for each sentence and transform them into a form suitable for training a particular syntactic parser. In this study, the object language is Czech, where sentence diagrams are part of elementary school curriculum, and the target format is the annotation scheme of the Prague Dependency Treebank. We mainly focus on the evaluation of individual diagrams and on their combination into a merged better version. 1
Informatique pour le Traitement Automatique des Langues Actes de la conférence TALN-RÉCITAL 2013 Volume 2: RÉCITAL 2013
, 2013
"... Sous l’égide de l’ATALA (Association pour le Traitement Automatique des langues). ii Avant-propos Il est maintenant une tradition dans la communauté de l’ATALA de venir fouler tous les dix ans les côtes à l’ouest de la France. Ainsi après la Côte d’Amour en 2003, nous sommes heureux d’accueillir sur ..."
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Sous l’égide de l’ATALA (Association pour le Traitement Automatique des langues). ii Avant-propos Il est maintenant une tradition dans la communauté de l’ATALA de venir fouler tous les dix ans les côtes à l’ouest de la France. Ainsi après la Côte d’Amour en 2003, nous sommes heureux d’accueillir sur la Côte de Lumière la 20e conférence TALN et la 15e édition de RÉCITAL. L’organisation de TALN et RÉCITAL 2013 a été assurée par les équipes TALN du LINA (Laboratoire d’Informatique de Nantes Atlantique) et LST du LIUM (Laboratoire d’Infor-matique de l’Université du Maine). Cette organisation conjointe est une bonne illustration de la synergie de ces deux équipes mais aussi de la dynamique du TALN dans la région des Pays de la Loire. Cette année, avec 127 soumissions à TALN (dont 70 articles longs et 57 articles courts), la conférence a confirmé une fois encore son attractivité. Le processus d’évaluation, qui a de-mandé un travail important, a été réalisé consciencieusement pour arriver à une sélection
