Linear temporal logic (LTL) is commonly used in model checking tasks; moreover, it is well-
suited for the formalization of technical requirements. However, the correct specification and …

Temporal reasoning is a crucial natural language processing (NLP) task, providing a
nuanced understanding of time-sensitive contexts within textual data. Although recent …

Time expression (aka, timex) recognition and normalization (TERN) is a crucial task for
downstream research. However, previous studies have overlooked the critical …

Existing unsupervised word embedding methods have been proved to be effective to
capture latent semantic information on various tasks of Natural Language Processing (NLP) …

Although temporal tagging is still dominated by rule-based systems, there have been recent
attempts at neural temporal taggers. However, all of them focus on monolingual settings. In …

Time information plays an important role in the areas of data mining, information retrieval,
and natural language processing. Among the linguistic tasks related to time expressions …

Objective The goal of this study is to develop a robust Time Event Ontology (TEO), which can
formally represent and reason both structured and unstructured temporal information …

This paper presents our approach for the 2024 ChemoTimelines shared task. Specifically,
we explored using Large Language Models (LLMs) for temporal relation extraction. We …

News events are often associated with quantities (eg, the number of COVID-19 patients or
the number of arrests in a protest), and it is often important to extract their type, time, and …

Temporal expressions in text play a significant role in language understanding and correctly
identifying them is fundamental to various retrieval and natural language processing …