Analysis of errors in the automatic translation of questions for translingual QA systems

Purpose – This study aims to focus on the evaluation of systems for the automatic translation of questions destined to translingual question-answer (QA) systems. The efficacy of online translators when performing as tools in QA systems is analysed using a collection of documents in the Spanish language. Design/methodology/approach – Automatic translation is evaluated in terms of the functionality of actual translations produced by three online translators (Google Translator, Promt Translator, and Worldlingo) by means of objective and subjective evaluation measures, and the typology of errors produced was identified. For this purpose, a comparative study of the quality of the translation of factual questions of the CLEF collection of queries was carried out, from German and French to Spanish. Findings – It was observed that the rates of error for the three systems evaluated here are greater in the translations pertaining to the language pair German-Spanish. Promt was identified as the most reliable translator of the three (on average) for the two linguistic combinations evaluated. However, for the Spanish-German pair, a good assessment of the Google online translator was obtained as well. Most errors (46.38 percent) tended to be of a lexical nature, followed by those due to a poor translation of the interrogative particle of the query (31.16 percent). Originality/value – The evaluation methodology applied focuses above all on the finality of the translation. That is, does the resulting question serve as effective input into a translingual QA system? Thus, instead of searching for “perfection”, the functionality of the question and its capacity to lead one to an adequate response are appraised. The results obtained contribute to the development of improved translingual QA systems

Analysis of automatic translation of questions for question-answering systems

Multilingual question-answering systems can provide users with specific data in response to queries by searching for a minimal fragment of text that applies to the query, regardless of the language in which the question is formulated and the answer is found. The aim of this paper is to analyse the automatic translation of questions (intended as queries input to a cross-language, question-answering system) from German and French into the Spanish language. Method. The methodology used for evaluation, based on automatic and subjective measures, appraises whether the translation will serve as input to a system. That is, does the question retain its validity and fulfil its function, allowing a proper response to be found? Analysis. The main features of multilingual question-answering systems are described and then we analyse the effectiveness of the translations achieved through three popular online translating tools: Google Translator, Promt and Worldlingo. Results. Our findings serve to identify which is the most reliable translator for both pairs of languages overall. However, an even more reliable option would be to use two different translators, depending on which of the two source languages is being dealt with. Conclusions. The results contribute to the realm of innovative search systems by enhancing our understanding of online translators and their potential in the context of multilingual information retrieval

Analysis of automatic translation of questions for question-answering systems

Introduction. Multilingual question-answering systems can provide users with specific data in response to queries by searching for a minimal fragment of text that applies to the query, regardless of the language in which the question is formulated and the answer is found. The aim of this paper is to analyse the automatic translation of questions (intended as queries input to a cross-language, question-answering system) from German and French into the Spanish language. Method. The methodology used for evaluation, based on automatic and subjective measures, appraises whether the translation will serve as input to a system. That is, does the question retain its validity and fulfil its function, allowing a proper response to be found? Analysis. The main features of multilingual question-answering systems are described and then we analyse the effectiveness of the translations achieved through three popular online translating tools: Google Translator, Promt and Worldlingo. Results. Our findings serve to identify which is the most reliable translator for both pairs of languages overall. However, an even more reliable option would be to use two different translators, depending on which of the two source languages is being dealt with. Conclusions. The results contribute to the realm of innovative search systems by enhancing our understanding of online translators and their potential in the context of multilingual information retrieval

An overview of the linguistic resources used in cross-language question answering systems in CLEF Conference

The development of the Semantic Web requires great economic and human effort. Consequently, it is very useful to create mechanisms and tools that facilitate its expansion. From the standpoint of information retrieval (hereafter IR), access to the contents of the Semantic Web can be favored by the use of natural language, as it is much simpler and faster for the user to engage in his habitual form of expression. The growing popularity of Internet and the wide availability of web informative resources for general audiences are a fairly recent phenomenon, although man´s need to hurdle the language barrier and communicate with others is as old as the history of mankind. The World Wide Web, also known as WWW, together with the growing globalization of companies and organizations, and the increase of the non-English speaking audience, entails the demand for tools allowing users to secure information from a wide range of resources. Yet the underlying linguistic restrictions are often overlooked by researchers and designers. Against this background, a key characteristic to be evaluated in terms of the efficiency of IR systems is its capacity to allow users find a corpus of documents in different languages, and to facilitate the relevant information despite limited linguistic competence regarding the target language

Language Resources Used in Multi-Lingual Question Answering Systems

Purpose – In the field of information retrieval, some multi-lingual tools are being created to help the users to overcome the language barriers. Nevertheless, these tools are not developed completely and it is necessary to investigate more for their improvement and application. One of their main problems is the choice of the linguistic resources to offer better coverage and to solve the translation problems in the context of the multi-lingual information retrieval. This paper aims to address this issue. Design/methodology/approach – This research is focused on the analysis of resources used by the multi-lingual question-answering systems, which respond to users' queries with short answers, rather than just offering a list of documents related to the search. An analysis of the main publications about the multi-lingual QA systems was carried out, with the aim of identifying the typology, the advantages and disadvantages, and the real use and trend of each of the linguistic resources and tools used in this new kind of system. Findings – Five of the resources most used in the cross-languages QA systems were identified and studied: databases, dictionaries, corpora, ontologies and thesauri. The three most popular traditional resources (automatic translators, dictionaries, and corpora) are gradually leaving a widening gap for others – such as ontologies and the free encyclopaedia Wikipedia. Originality/value – The perspective offered by the translation discipline can improve the effectiveness of QA system

An Overview of the Linguistic Resources used in Cross-Language Question Answering Systems in CLEF Conference

The development of the Semantic Web requires great economic and human effort. Consequently, it is very useful to create mechanisms and tools that facilitate its expansion. From the standpoint of information retrieval (hereafter IR), access to the contents of the Semantic Web can be favored by the use of natural language, as it is much simpler and faster for the user to engage in his habitual form of expression. The growing popularity of Internet and the wide availability of web informative resources for general audiences are a fairly recent phenomenon, although man´s need to hurdle the language barrier and communicate with others is as old as the history of mankind. The World Wide Web, also known as WWW, together with the growing globalization of companies and organizations, and the increase of the non-English speaking audience, entails the demand for tools allowing users to secure information from a wide range of resources. Yet the underlying linguistic restrictions are often overlooked by researchers and designers. Against this background, a key characteristic to be evaluated in terms of the efficiency of IR systems is its capacity to allow users find a corpus of documents in different languages, and to facilitate the relevant information despite limited linguistic competence regarding the target language