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Graph-based semantic parsing aims to represent textual meaning through directed graphs. As one of the most promising general-purpose meaning representations, these structures and their parsing have gained a significant interest momentum during recent years, with several diverse formalisms being proposed. Yet, owing to this very heterogeneity, most of the research effort has focused mainly on solutions specific to a given formalism. In this work, instead, we reframe semantic parsing towards multiple formalisms as Multilingual Neural Machine Translation (MNMT), and propose SGL, a many-to-many seq2seq architecture trained with an MNMT objective. Backed by several experiments, we show that this framework is indeed effective once the learning procedure is enhanced with large parallel corpora coming from Machine Translation: we report competitive performances on AMR and UCCA parsing, especially once paired with pre-trained architectures. Furthermore, we find that models trained under this configuration scale remarkably well to tasks such as cross-lingual AMR parsing: SGL outperforms all its competitors by a large margin without even explicitly seeing non-English to AMR examples at training time and, once these examples are included as well, sets an unprecedented state of the art in this task. We release our code and our models for research purposes at https://github.com/SapienzaNLP/sgl.

In Text-to-AMR parsing, current state-of-the-art semantic parsers use cumbersome pipelines integrating several different modules or components, and exploit graph recategorization, i.e., a set of content-specific heuristics that are developed on the basis of the training set. However, the generalizability of graph recategorization in an out-of-distribution setting is unclear. In contrast, state-of-the-art AMR-to-Text generation, which can be seen as the inverse to parsing, is based on simpler seq2seq. In this paper, we cast Text-to-AMR and AMR-to-Text as a symmetric transduction task and show that by devising a careful graph linearization and extending a pretrained encoder-decoder model, it is possible to obtain state-of-the-art performances in both tasks using the very same seq2seq approach, i.e., SPRING (Symmetric PaRsIng aNd Generation). Our model does not require complex pipelines, nor heuristics built on heavy assumptions. In fact, we drop the need for graph recategorization, showing that this technique is actually harmful outside of the standard benchmark. Finally, we outperform the previous state of the art on the English AMR 2.0 dataset by a large margin: on Text-to-AMR we obtain an improvement of 3.6 Smatch points, while on AMR-to-Text we outperform the state of the art by 11.2 BLEU points. We release the software at github.com/SapienzaNLP/spring.

AbstractThe archaeological site of Lepenski Vir is widely known after its remarkable stone art sculptures that represent a unique and unprecedented case of Holocene hunter-gatherer creativity. These artworks were found largely associated with equally unique trapezoidal limestone building floors around their centrally located rectangular stone-lined hearths. A debate has raged since the discovery of the site about the chronological place of various discovered features. While over years different views from that of the excavator about the stratigraphy and chronology of the site have been put forward, some major disagreements about the chronological position of the features that make this site a key point of reference in European Prehistory persist. Despite challenges of re-analyzing the site’s stratigraphy from the original excavation records, taphonomic problems, and issues of reservoir offsets when providing radiocarbon measurements on human and dog bones, our targeted AMS (Accelerator Mass Spectrometry) dating of various contexts from this site with the application of Bayesian statistical modelling allows us to propose with confidence a new and sound chronological framework and provide formal estimates for several key developments represented in the archaeological record of Lepenski Vir that help us in understanding the transition of last foragers to first farmers in southeast Europe as a whole.

The knowledge acquisition bottleneck strongly affects the creation of multilingual sense-annotated data, hence limiting the power of supervised systems when applied to multilingual Word Sense Disambiguation. In this paper, we propose a semi-supervised approach based upon a novel label propagation scheme, which, by jointly leveraging contextualized word embeddings and the multilingual information enclosed in a knowledge base, projects sense labels from a high-resource language, i.e., English, to lower-resourced ones. Backed by several experiments, we provide empirical evidence that our automatically created datasets are of a higher quality than those generated by other competitors and lead a supervised model to achieve state-of-the-art performances in all multilingual Word Sense Disambiguation tasks. We make our datasets available for research purposes at https://github.com/SapienzaNLP/mulan.

European cultural heritage (CH) is at risk, threatened by environmental processes strengthened by climate change and anthropogenic pressure. In particular, the slow (landslides, subsidence) and seismic (earthquakes) movements of the soil have a strong impact on the structural stability of our cultural heritage (CH). The actions to be carried out to protect and safeguard CH are in continuous development and this is where the STABLE (STructural stABiLity risk assEssment) project fits. STABLE concerns the design and development of a thematic platform, which combines structural stability models, simulation and damage assessment tools, advanced remote sensing, in situ monitoring technologies, geotechnical and cadastral data sets with the WebGIS application for mapping and long-term monitoring of the CH. The thematic platform, which is the final objective of the project, will therefore support the authorities responsible for the conservation of cultural heritage in the design and implementation of policies for monitoring, preserving and safeguarding our heritage. This will allow effective monitoring and management of CH to prevent or at least reduce the possible irreparable damages. STABLE will coordinate existing skills and research in a synergistic plan of collaborations and staff exchanges to offer a complete transfer of knowledge and training to researchers in the specific area under study. The development of the platform will be the strategy that scientists will have to follow to share and improve CH safeguard methods. It will serve professionals to apply the most advanced technologies in their fields.

Contextualized word embeddings have been employed effectively across several tasks in Natural Language Processing, as they have proved to carry useful semantic information. However, it is still hard to link them to structured sources of knowledge. In this paper we present ARES (context-AwaRe Embeddings of Senses), a semi-supervised approach to producing sense embeddings for the lexical meanings within a lexical knowledge base that lie in a space that is comparable to that of contextualized word vectors. ARES representations enable a simple 1 Nearest-Neighbour algorithm to outperform state-of-the-art models, not only in the English Word Sense Disambiguation task, but also in the multilingual one, whilst training on sense-annotated data in English only. We further assess the quality of our embeddings in the Word-in-Context task, where, when used as an external source of knowledge, they consistently improve the performance of a neural model, leading it to compete with other more complex architectures. ARES embeddings for all WordNet concepts and the automatically-extracted contexts used for creating the sense representations are freely available at http://sensembert.org/ares.

AbstractThis paper provides results from a suite of analyses made on human dental material from the Late Palaeolithic to Neolithic strata of the cave site of Grotta Continenza situated in the Fucino Basin of the Abruzzo region of central Italy. The available human remains from this site provide a unique possibility to study ways in which forager versus farmer lifeways affected human odonto-skeletal remains. The main aim of our study is to understand palaeodietary patterns and their changes over time as reflected in teeth. These analyses involve a review of metrics and oral pathologies, micro-fossils preserved in the mineralized dental plaque, macrowear, and buccal microwear. Our results suggest that these complementary approaches support the assumption about a critical change in dental conditions and status with the introduction of Neolithic foodstuff and habits. However, we warn that different methodologies applied here provide data at different scales of resolution for detecting such changes and a multipronged approach to the study of dental collections is needed for a more comprehensive and nuanced understanding of diachronic changes.

The native groups of Patagonia have relied on a hunter-gatherer economy well after the first Europeans and North Americans reached this part of the world. The large exploitation of marine mammals (i.e., seals) by such allochthonous groups has had a strong impact on the local ecology in a way that might have forced the natives to adjust their subsistence strategies. Similarly, the introduction of new foods might have changed local diet. These are the premises of our isotopic-based analysis. There is a large set of paleonutritional investigations through isotopic analysis on Fuegians groups, however a systematic exploration of food practices across time in relation to possible pre- A nd post-contact changes is still lacking. In this paper we investigate dietary variation in hunter-gatherer groups of Tierra del Fuego in a diachronic perspective, through measuring the isotopic ratio of carbon (∂13C) and nitrogen (∂15N) in the bone collagen of human and a selection of terrestrial and marine animal samples. The data obtained reveal an unexpected isotopic uniformity across prehistoric and recent groups, with little variation in both carbon and nitrogen mean values, which we interpret as the possible evidence of resilience among these groups and persistence of subsistence strategies, allowing inferences on the dramatic contraction (and extinction) of Fuegian populations. Fil: Tafuri, Mary Anne. Universita Di Roma; Italia Fil: Zangrando, Atilio Francisco Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina Fil: Tessone, Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Geocronología y Geología Isotopica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Geocronología y Geología Isotópica; Argentina Fil: Kochi, Sayuri. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Geocronología y Geología Isotopica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Geocronología y Geología Isotópica; Argentina Fil: Moggi, Augusto. Università degli Studi di Firenze; Italia Fil: Di Vincezo, Fabio. Università di Roma; Italia Fil: Profico, Antonio. Università di Roma; Italia Fil: Manzi, Giorgio. Università di Roma; Italia

AbstractStone tools provide a unique window into the mode of adaptation and cognitive abilities of Lower Paleolithic early humans. The persistently produced large cutting tools (bifaces/handaxes) have long been an appealing focus of research in the reconstruction of Lower Paleolithic survival strategies, at the expenses of the small flake tools considered by-products of the stone production process rather than desired end products. Here, we use use-wear, residues and technological analyses to show direct and very early evidence of the deliberate production and use of small flakes for targeted stages of the prey butchery process at the late Lower Paleolithic Acheulian site of Revadim, Israel. We highlight the significant role of small flakes in Lower Paleolithic adaptation alongside the canonical large handaxes. Our results demonstrate the technological and cognitive flexibility of early human groups in the Levant and beyond at the threshold of the departure from Lower Paleolithic lifeways.