1,144 research outputs found
Specificity ratings for English data
No full textA dataset of specificity ratings for English words is hereby presented, analyzed and discussed in relation with other collections of speaker-generated ratings, including concreteness. Both, specificity and concreteness are analyzed in their ability to explain decision latencies in lexical and semantic tasks, showing important individual contributions. Specificity ratings are collected through best–worst scaling method on the words included in the ANEW dataset (Bradley and Lang in Affective norms for English words (ANEW): instruction manual and affective ratings (Tech. Rep.). Technical report C-1, the center for research in psychophysiology, 1999), chosen for its compatibility with many other collections of rating resources, and for its comparability with Italian specificity data (Bolognesi and Caselli in Behav Res Methods 55(7):3531–3548, 2023), allowing for cross-linguistic comparisons. Results suggest that specificity plays an important role in word processing and the importance of taking specificity into consideration when investigating concreteness effects
Crescentino Caselli e il sistema costruttivo antonelliano: le innovazioni nella Piccola Casa della Divina Provvidenza
No full textIl contributo indaga l’approccio innovativo alla progettazione adottato da Crescentino Caselli e le sue evidenze riscontrabili nella Piccola Casa della Divina Provvidenza di Vinovo, al fine di orientare eventuali interventi di restauro architettonico verso una progettazione che sia innanzitutto consapevole dei caratteri peculiari del bene stesso. Si intende porre in luce quegli elementi propri del metodo antonelliano, definito da Caselli come «il germe vivificatore di nuovi progressi dell’architettura italiana», evidenziando gli ulteriori sviluppi introdotti dall’ingegnere stesso. In particolare, si vuole approfondire lo schema strutturale dell’edificio, analizzando il sistema dei fulcri, dei muri perimetrali, degli archi e delle volte nell’intento di restituire un quadro complessivo delle innovazioni che il sistema antonelliano introdusse nel mondo delle strutture in laterizio
Crowdsourcing Temporal Relations in Italian and English
No full textThis paper reports on two crowdsourcing experiments on Temporal Relation Annotation in Italian and English. The aim of these experiments is three-fold: first, to evaluate average Italian and English native speakers on their ability to identify and classify a temporal relation between two verbal events; second, to assess the feasibility of crowdsourcing for this kind of complex semantic task; third to perform a preliminary analysis of the role of syntax within such task. Two categories of temporal relations were investigated: relations between the main event and its subordinated event (e.g. So che hai visto Giovanni / I know you’ve seen John) and relations between two main events (e.g. Giovanni bussò ed entrò / John knocked and got in). Fifty aligned parallel sentences in the two languages from the MultiSemCor corpus were extracted. In each sentence, the source and the target verbs of the relations were highlighted and contributors were asked to select the temporal relation from 7 values (AFTER, BEFORE, INCLUDES, IS INCLUDED, SIMULTANEOUS, NO RELATION, and DON’T KNOW) inspired by the TimeML Annotation Guidelines. For each sentence, 5 judgments were collected. The results of the annotator agreement is 0.41 for Italian and 0.32 for English. Analysis of the data has shown that annotating temporal relations is not a trivial task and that dependency relations between events have a major role in facilitating the annotation. Future work aims at conducting new experiments with an additional parameter, namely factivity, and with texts in a different domain, i.e. History
Specificity ratings for Italian data
Full text linkAbstraction enables us to categorize experience, learn new information, and form judgments. Language arguably plays a crucial role in abstraction, providing us with words that vary in specificity (e.g., highly generic: tool vs. highly specific: muffler). Yet, human-generated ratings of word specificity are virtually absent. We hereby present a dataset of specificity ratings collected from Italian native speakers on a set of around 1K Italian words, using the Best-Worst Scaling method. Through a series of correlation studies, we show that human-generated specificity ratings have low correlation coefficients with specificity metrics extracted automatically from WordNet, suggesting that WordNet does not reflect the hierarchical relations of category inclusion present in the speakers’ minds. Moreover, our ratings show low correlations with concreteness ratings, suggesting that the variables Specificity and Concreteness capture two separate aspects involved in abstraction and that specificity may need to be controlled for when investigating conceptual concreteness. Finally, through a series of regression studies we show that specificity explains a unique amount of variance in decision latencies (lexical decision task), suggesting that this variable has theoretical value. The results are discussed in relation to the concept and investigation of abstraction.</p
Crowdsourcing Temporal Relations in Italian and English
No full textThis paper reports on two crowdsourcing experiments on Temporal Relation Annotation in Italian and English. The aim of these experiments is three-fold: first, to evaluate average Italian and English native speakers on their ability to identify and classify a temporal relation between two verbal events; second, to assess the feasibility of crowdsourcing for this kind of complex semantic task; third to perform a preliminary analysis of the role of syntax within such task. Two categories of temporal relations were investigated: relations between the main event and its subordinated event (e.g. So che hai visto Giovanni / I know you’ve seen John) and relations between two main events (e.g. Giovanni bussò ed entrò / John knocked and got in). Fifty aligned parallel sentences in the two languages from the MultiSemCor corpus were extracted. In each sentence, the source and the target verbs of the relations were highlighted and contributors were asked to select the temporal relation from 7 values (AFTER, BEFORE, INCLUDES, IS INCLUDED, SIMULTANEOUS, NO RELATION, and DON’T KNOW) inspired by the TimeML Annotation Guidelines. For each sentence, 5 judgments were collected. The results of the annotator agreement is 0.41 for Italian and 0.32 for English. Analysis of the data has shown that annotating temporal relations is not a trivial task and that dependency relations between events have a major role in facilitating the annotation. Future work aims at conducting new experiments with an additional parameter, namely factivity, and with texts in a different domain, i.e. History
Content Type Dataset - v1.5
No full textThis repository contains:
- the Content Type Dataset Version 1.5 (in the folder "Datasets");
- the latest version of the guidelines for annotating Content Types;
- the data statement related to CTD V1.5;
- a set of spreadsheets containing metadata about the documents included in the dataset, e.g. year of publication, author's name, author's nationality, author's gender (in the folder "Documents_Metadata");
- the data to replicate a set of experiments for the identification of Content Types (in the folder "Datasets");
- the best model for the identification of Content Types obtained adopting the BiLSTM-CNN-CRF with ELMo-Representations for Sequence Tagging implementation by Nils Reimers and Iryna Gurevych (in the folder "Best_Model");
- the data used to calculate the Inter-Annotator Agreement (in the folder "IAA"): the script used for calculating Cohen's k is available here: https://github.com/johnnymoretti/CAT_R_Kappa_Cohe
A Narratology-Based Framework for Storyline Extraction
Full text linkStories are a pervasive phenomenon of human life. They also represent a cognitive tool to understand and make sense of the world and of its happenings. In this contribution we describe a narratology-based framework for modeling stories as a combination of different data structures and to automatically extract them from news articles. We introduce a distinction among three data structures (timelines, causelines, and storylines) that capture different narratological dimensions, respectively chronological ordering, causal connections, and plot structure. We developed the Circumstantial Event Ontology (CEO) for modeling (implicit) circumstantial relations as well as explicit causal relations and create two benchmark corpora: ECB+/CEO, for causelines, and the Event Storyline Corpus (ESC), for storylines. To test our framework and the difficulty in automatically extract causelines and storylines, we develop a series of reasonable baseline system
Lettera di Alessandra
No full textUn ritratto critico dell'opera di Alessandra Carnaroli, autrice fra le più apprezzate delle ultime generazioni della poesia di ricerca. La sezione a lei dedicata, nel numero della rivista, contiene inoltre saggi di Cecilia Bello Minciacchi, Andrea Cortellessa, e Ivan Schiavone; e vari inediti dell'autrice. Il saggio è pubblicato con lo pseudonimo di Tommaso Ottonieri.A critical portrait of the work of Alessandra Carnaroli, author of the most appreciated in the latest generations of italian research poetry. Published under the pseudonym Tommaso Ottonieri
It-TimeML and the Ita-TimeBank: Language Specific Adaptations for Temporal Annotation
No full textThis chapter presents the language specific adaptation of the TimeML annotation scheme to Italian and the creation of the Ita-TimeBank, a language resource composed of two corpora manually annotated with temporal and event information. Particular attention is given to the methodology followed in the development of the corpora: the annotation guidelines document the actual choices done during the annotation and address language specific issues while maintaining adherence to the specifications. The annotation guidelines are supplied with decision tree like instructions and tests grounded in linguistic analysis but theory independent. The results obtained show the reliability of the adaptation of the annotation specifications to Italian and of the methodology used for the creation of the resources
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