Variation and Semantic Relation Interpretation: Linguistic and Processing Issues

International audienceStudies in linguistics define lexico-syntactic patterns to characterize the linguistic utterances that can be interpreted with semantic relations. Because patterns are assumed to reflect linguistic regularities that have a stable interpretation, several software implement such patterns to extract semantic relations from text. Nevertheless, a thorough analysis of pattern occurrences in various corpora proved that variation may affect their interpretation. In this paper, we report the linguistic variations that impact relation interpretation in language, and may lead to errors in relation extraction systems. We analyze several features of state-of-the-art pattern-based relation extraction tools, mostly how patterns are represented and matched with text, and discuss their role in the tool ability to manage variation

Text Analytics for Android Project

Most advanced text analytics and text mining tasks include text classification, text clustering, building ontology, concept/entity extraction, summarization, deriving patterns within the structured data, production of granular taxonomies, sentiment and emotion analysis, document summarization, entity relation modelling, interpretation of the output. Already existing text analytics and text mining cannot develop text material alternatives (perform a multivariant design), perform multiple criteria analysis, automatically select the most effective variant according to different aspects (citation index of papers (Scopus, ScienceDirect, Google Scholar) and authors (Scopus, ScienceDirect, Google Scholar), Top 25 papers, impact factor of journals, supporting phrases, document name and contents, density of keywords), calculate utility degree and market value. However, the Text Analytics for Android Project can perform the aforementioned functions. To the best of the knowledge herein, these functions have not been previously implemented; thus this is the first attempt to do so. The Text Analytics for Android Project is briefly described in this article

Discourse Strategies in the Teaching of English Writing

This paper explores the text types, text patterns and text topic continuity which may be found in texts which are the objects of interpretation by the reader, and they are often signaled by the grammatical and lexical devices. So they are very useful for the teaching of writing

Discourse relations and defeasible knowledge

This paper presents a formal account of the temporal interpretation of text. The distinct nat- ural interpretations of texts with similar syntax are explained in terms of defeasible rules charac- tcrising causal laws and Gricean-style pragmatic maxims. Intuitively compelling patterns of defea. sible entaJlment that are supported by the logic in which the theory is expressed are shown to underly temporal interpretation

An automated identification and analysis of ontological terms in gastrointestinal diseases and nutrition-related literature provides useful insights

With an unprecedented growth in the biomedical literature, keeping up to date with the new developments presents an immense challenge. Publications are often studied in isolation of the established literature, with interpretation being subjective and often introducing human bias. With ontology-driven annotation of biomedical data gaining popularity in recent years and online databases offering metatags with rich textual information, it is now possible to automatically text-mine ontological terms and complement the laborious task of manual management, interpretation, and analysis of the accumulated literature with downstream statistical analysis. In this paper, we have formulated an automated workflow through which we have identified ontological information, including nutrition-related terms in PubMed abstracts (from 1991 to 2016) for two main types of Inflammatory Bowel Diseases: Crohn’s Disease and Ulcerative Colitis; and two other gastrointestinal (GI) diseases, namely, Coeliac Disease and Irritable Bowel Syndrome. Our analysis reveals unique clustering patterns as well as spatial and temporal trends inherent to the considered GI diseases in terms of literature that has been accumulated so far. Although automated interpretation cannot replace human judgement, the developed workflow shows promising results and can be a useful tool in systematic literature reviews. The workflow is available at https://github.com/KociOrges/pytag

Computational Literary Genre Stylistics

The project in a nutshell: This project will investigate the relation between literary genres (generic facets) and style (stylistic attributes). Analyses are based on large collections of literary texts and use or develop state-of-the-art methods in computational stylistics and text analysis. This will enable the project to combine attention to minute stylistic details with the investigation of large trends and patterns in literary history. What does the project aim to accomplish? The project brings together scholars from Romance Philology and Computer Scientists, building a common ground in Computational Philology. It aims to change the way we think about the concepts of genre and style as well as about the relation between literary interpretation and computation. In particular, the project aims to strengthen the engagement with digital methods in Romance Philology

“Ab-Soul’s Outro,” “HiiiPower,” and the Vernacular: Kendrick Lamar’s Rap As Literature

Kendrick Lamar’s “Ab-Soul’s Outro” and “HiiiPower” employ complex patterns of Signifyin(g), testifyin’, and other classical African-American literary tropes in order to construct a nuanced style. Lamar creates a double-voiced text not only within his narrative, but also within the form itself. Lamar plays on rap\u27s unique status in African-American literature as an oral text; it is an extension of the vernacular. Through this oral text, Lamar decentralizes the Eurocentric focus of classical interpretation and qualification of literature to a new Afrocentric perspective that privileges the oral text. These raps are complex, wrapped up in their current context along with a deeply rooted historical and literary context. Closely read, the raps function as liminal texts, straddling the horizons of music and literature as well as the horizons of white and black literary conventions. Because of this complexity, Lamar’s tracks transcend the techniques of interpretation readily applicable to music and thus can be classified as literature

QAKiS @ QALD-2

International audienceWe present QAKiS, a system for Question Answering over linked data (in particular, DBpedia). The problem of question interpretation is addressed as the automatic identification of the set of relevant relations between entities in the natural language input question, matched against a repository of automatically collected relational patterns (i.e. the WikiFramework repository). Such patterns represent possible lexical-izations of ontological relations, and are associated to a SPARQL query derived from the linked data relational patterns. Wikipedia is used as the source of free text for the automatic extraction of the relational patterns, and DBpedia as the linked data resource to provide relational patterns and to be queried using a natural language interface