Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).

De l’expressió de la percepció sensorial auditiva a l’expressió del discurs reportat. El verb sentir en català medieval (s. XIII–XVI)

This study analyzes the process of semantic change by which the Old Catalan verb sentir developed from a meaning based on general perception to one implying auditory perception. In particular, the article shows that by the end of the 13th century the verb sentir had only semanticized the perception of non-linguistic auditory stimuli and had not fused completely with the meaning of the verb oir, as was the case with the evolution of SĔNTĪRE in other Romance languages (such as Peninsular Spanish). Our study has been based on data analysis of an electronic linguistic corpus using the concepts of E. C. Traugott’s Invited Inferencing Theory of Semantic Change (IITSC) (2012) and the concept of evidentiality.

Computational approach to anaphora resolution in Spanish dialogues

This paper presents an algorithm for identifying noun-phrase antecedents of pronouns and adjectival anaphors in Spanish dialogues. We believe that anaphora resolution requires numerous sources of information in order to find the correct antecedent of the anaphor. These sources can be of different kinds, e.g., linguistic information, discourse/dialogue structure information, or topic information. For this reason, our algorithm uses various different kinds of information (hybrid information). The algorithm is based on linguistic constraints and preferences and uses an anaphoric accessibility space within which the algorithm finds the noun phrase. We present some experiments related to this algorithm and this space using a corpus of 204 dialogues. The algorithm is implemented in Prolog. According to this study, 95.9% of antecedents were located in the proposed space, a precision of 81.3% was obtained for pronominal anaphora resolution, and 81.5% for adjectival anaphora.

Subjectivació i interferència en l'evolució semàntica i en l'inici de la gramaticalització de "jaquir" (segles XI-XII)

Estudiem en aquest article els primers passos en l'evolució semàntica i en la gramaticalització del verb "jaquir". Aquest germanisme pertany a un estrat lèxic del català que va començar a fer-se menys usual a la darreria del segle XV, desplaçat per altres sinònims, en aquest cas lleixar-deixar. La recerca es fonamenta en un corpus de documentació en llatí i en català dels segles XI i XII. L'objectiu és descriure la gènesi dels significats que ja apareixen ben establits durant el període literari. Seguim un enfocament metodològic d'orientació cognitivista (estudi de la subjectivació i de la inferència com a mecanismes del canvi semàntic).

Diacronia i neologia: canvi semàntic, subjectivació i representació del pensament. El català esmar, des de ‘taxar’ fins a ‘inferir’ i ‘imaginar’ i més enllà

L’estudi de la neologia és indestriable de l’estudi del canvi lingüístic i, doncs, de la diacronia. Ens proposem ací descriure el procés de canvi semàntic que va experimentar el verb esmar, forma patrimonial del llatí *adaestimare, paral·lela del cultisme estimar. Aquesta recerca es fonamenta en l’aprofitament dels corpus textuals i altres materials despullats manualment. Sobre aquests materials, s’ha assajat l’anàlisi de la subjectivació i de les inferències que proposa la teoria de la inferència invitada del canvi semàntic (= TIICS).

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.