Argument Structure in TimeML

TimeML is a specification language for the annotation of events and temporal expressions in natural language text. In addition, the language introduces three relational tags linking temporal objects and events to one another. These links impose both aspectual and temporal ordering over time objects, as well as mark up subordination contexts introduced by modality, evidentiality, and factivity. Given the richness of this specification, the TimeML working group decided not to include the arguments of events within the language specification itself. Full reasoning and inference over natural language texts clearly requires knowledge of events along with their participants. In this paper, we define the appropriate role of argumenthood within event markup and propose that TimeML should make a basic distinction between arguments that are events and those that are entities. We first review how TimeML treats event arguments in subordinating and aspectual contexts, creating event-event relations between predicate and argument. As it turns out, these constructions cover a large number of the argument types selected for by event predicates. We suggest that TimeML be enriched slightly to include causal predicates, such as {it lead to}, since these also involve event-event relations. We propose that all other verbal arguments be ignored by the specification, and any predicate-argument binding of participants to an event should be performed by independent means. In fact, except for the event-denoting arguments handled by the extension to TimeML proposed here, almost full temporal ordering of the events in a text can be computed without argument identification

Mudbricks, Construction Methods, and Stratigraphic Analysis : A Case Study at Tell Timai (ancient Thmuis) in the Egyptian Delta

The Graeco-Roman site of Tell Timai (ancient Thmuis) in Lower Egypt is among the largest urban tells in the Nile Delta, boasting substantial amounts of preserved earthen architecture. Although earthen architecture made up the vast majority of public and domestic structures in ancient Egypt, it still does not receive the same analytical attention from archaeologists as other categories of evidence. This paper presents a case study for the archaeological investigation of the earthen architecture at Tell Timai. The goal was to develop a methodology that can be implemented in the field by excavators with little geoarchaeological training and limited laboratory access in order to generate useful data for determining building stratigraphy and studying construction processes. Through the close examination and sampling of three buildings of different periods and scales, we tested a new field methodology combining geoarchaeological techniques and mensiochronology. The results provide information useful for stratigraphy and phasing as well as for identifying specific patterns of mudbrick manufacturing, production, and construction during the Graeco-Roman period at Tell Timai.Peer reviewe

Gut Microbiome Dysbiosis in Antibiotic-Treated COVID-19 Patients is Associated with Microbial Translocation and Bacteremia

Although microbial populations in the gut microbiome are associated with COVID-19 severity, a causal impact on patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. We first demonstrate SARS-CoV-2 infection induces gut microbiome dysbiosis in mice, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, including blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19

Argument structure in TimeML

Abstract. TimeML is a specification language for the annotation of events and temporal expressions in natural language text. In addition, the language introduces three relational tags linking temporal objects and events to one another. These links impose both aspectual and temporal ordering over time objects, as well as mark up subordination contexts introduced by modality, evidentiality, and factivity. Given the richness of this specification, the TimeML working group decided not to include the arguments of events within the language specification itself. Full reasoning and inference over natural language texts clearly requires knowledge of events along with their participants. In this paper, we define the appropriate role of argumenthood within event markup and propose that TimeML should make a basic distinction between arguments that are events and those that are entities. We first review how TimeML treats event arguments in subordinating and aspectual contexts, creating event-event relations between predicate and argument. As it turns out, these constructions cover a large number of the argument types selected for by event predicates. We suggest that TimeML be enriched slightly to include causal predicates, such as lead to, since these also involve event-event relations. We propose that all other verbal arguments be ignored by the specification, and any predicate-argument binding of participants to an event should be performed by independent means. In fact, except for the event-denoting arguments handled by the extension to TimeML proposed here, almost full temporal ordering of the events in a text can be computed without argument identification

Towards a Generative Lexical Resource: The Brandeis Semantic Ontology

In this paper we describe the structure and development of the Brandeis Semantic Ontology (BSO), a large generative lexicon ontology and lexical database. The BSO has been designed to allow for more widespread access to Generative Lexicon-based lexical resources and help researchers in a variety of computational tasks. The specification of the type system used in the BSO largely follows that proposed by the SIMPLE specification (Busa et al., 2001), which was adopted by the EU-sponsored SIMPLE project (Lenci et al., 2000)

Automating temporal annotation with TARSQI

We present an overview of TARSQI, a modular system for automatic temporal annotation that adds time expressions, events and temporal relations to news texts