Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with
temporal intent are a special class of practical importance, but have not received much …

Within the SemEval-2013 evaluation exercise, the TempEval-3 shared task aims to advance
research on temporal information processing. It follows on from TempEval-1 and-2, with: a …

QA TempEval shifts the goal of previous TempEvals away from an intrinsic evaluation
methodology toward a more extrinsic goal of question answering. This evaluation requires …

Determining whether a major societal event has already happened, is still on-going, or may
occur in the future is crucial for event prediction, timeline generation, and news …

TimeML is an annotation scheme for capturing temporal information in text. The developers
of TimeML built the TimeBank corpus to both validate the scheme and provide a rich dataset …

In this paper we describe ISO-TimeML, an expressive and interoperable specification
language for event and temporal expressions in natural language text. Besides annotating …

The automatic extraction of temporal information from written texts is pivotal for many Natural
Language Processing applications such as question answering, text summarisation and …

Temporal features, such as an explicit date and time or a time-specific event, employ
concise semantics for any kind of information retrieval. Therefore, temporal features should …

TimeML is an XML-based schema for annotating temporal information over discourse. The
standard has been used to annotate a variety of resources and is followed by a number of …

TimeML serves as a foundational annotation scheme for capturing temporal information
within textual data. Despite the availability of several gold-standard TimeML corpora, the …