This work proposes the integration of a temporal expressions recognition, resolution and normalization system into a question answering system for Spanish. Both question analysis and answer extraction stages have been adapted to the new capabilities for temporal detection and inference of the system. It has been evaluated by means of a corpus composed of questions that has been originally devel...

This report describes a minimalistic set of methods engineered to anchor clinical events onto a temporal space. Specifically, we describe methods to extract clinical events (e.g., Problems, Treatments and Tests), temporal expressions (i.e., time, date, duration, and frequency), and temporal links (e.g., Before, After, Overlap) between events and temporal entities. These methods are developed an...

Nowadays, the temporal aspects of natural language are receiving a great research interest. TimeML has been adopted as a standard for temporal information annotation by a large number of researchers. Available TimeML resources are very limited in size and in diversity of languages. This paper analyzes a combination of semantic roles and semantic networks information for improving this situation...

We present and demonstrate the updated version of the TARSQI Toolkit, a suite of temporal processing modules that extract temporal information from natural language texts. It parses the document and identifies temporal expressions, recognizes events, anchor events to temporal expressions and orders events relative to each other. The toolkit was previously demonstrated at COLING 2008, but has si...

We present an approach for detecting salient (important) dates in texts in order to automatically build event timelines from a search query (e.g. the name of an event or person, etc.). This work was carried out on a corpus of newswire texts in English provided by the Agence France Presse (AFP). In order to extract salient dates that warrant inclusion in an event timeline, we first recognize and...

Formalization of natural language metaphors is a notorious problem in artificial intelligence and other overlapping domains. It semantic vagueness that makes resistant to formulaic or algorithmic descriptions. Great effort has been invested into modeling computationally but the issue remains methodologically uncertain needs further research. This paper works on practical solution how metaphoric...

Objective: The aim of this research is to describe the processing neural response metaphors in individuals with autism spectrum disorder (ASD) speaking Turkish as their native language and form basis for further field.
 Methods: In study, a single case study method was used. data collected by means structured questionnaire. answers were recorded “Systematic Analysis Language Transcripts” (...

We introduce an annotation scheme for temporal expressions, and describe a method for resolving temporal expressions in print and broadcast news. The system, which is based on both hand-crafted and machine-learnt rules, achieves an 83.2% accuracy (Fmeasure) against hand-annotated data. Some initial steps towards tagging event chronologies are also described.