SUMMARY. We describe our experiments in participating to the EV aluation of Events aNd Temporal Information(EVENTI) task, for the EVALITA 2014 evaluation campaign. We used the HeidelTime tagger extended with a wrapper for the Tanl POS tagger and tokenizer of the Tanl suite. The rules for recognizing Italian temporal expressions were rewritten and extended after the submission, leading to a 10 point increase in F1 over the Italian rules in the HeidelTime distribution. RIASSUNTO. Nell’articolo descriviamo gli esperimenti svolti per la nostra partecipazione al task EValuation of Events aNd Temporal Information(EVENTI), nel’ambito della campagna di valutazione EVALITA 2014. Per il riconoscimento e norma...
This report describes the annotation guidelines for Italian of the TimeML specifications.Questo repo...
This paper presents ITA-Chronos, the system developed at FBK-irst to participate in the “Temporal E...
In this paper we describe the systems we used to participate in the task TAG-it of EVALITA 2020. The...
We describe our experiments in participating to the EValuation of Events aNd Temporal Information (E...
Questo report descrive il task EVENTI (EValuation of Events aNd Temporal Information) organizzato ne...
In this paper we present an end-to-end system for temporal processing of Italian texts based on a ma...
In this paper we will present an ongoing research on the development of a temporal expression tagger...
In this paper, we describe motivations and features of the TERN (Temporal Expression Recognition and...
English. In this paper, we describe our participation in the EVENTI task. We ad-dressed subtask A, t...
This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system f...
AbstractThe automatic extraction of temporal information from written texts is pivotal for many Natu...
The use of contextualised word embeddings allowed for a relevant performance increase for almost all...
Abstract Extraction and normalization of temporal expressions from documents are important steps tow...
In this paper we describe a system for the recognition and normalization of temporal expressions in ...
The use of contextualised word embeddings allowed for a relevant performance increase for almost all...
This report describes the annotation guidelines for Italian of the TimeML specifications.Questo repo...
This paper presents ITA-Chronos, the system developed at FBK-irst to participate in the “Temporal E...
In this paper we describe the systems we used to participate in the task TAG-it of EVALITA 2020. The...
We describe our experiments in participating to the EValuation of Events aNd Temporal Information (E...
Questo report descrive il task EVENTI (EValuation of Events aNd Temporal Information) organizzato ne...
In this paper we present an end-to-end system for temporal processing of Italian texts based on a ma...
In this paper we will present an ongoing research on the development of a temporal expression tagger...
In this paper, we describe motivations and features of the TERN (Temporal Expression Recognition and...
English. In this paper, we describe our participation in the EVENTI task. We ad-dressed subtask A, t...
This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system f...
AbstractThe automatic extraction of temporal information from written texts is pivotal for many Natu...
The use of contextualised word embeddings allowed for a relevant performance increase for almost all...
Abstract Extraction and normalization of temporal expressions from documents are important steps tow...
In this paper we describe a system for the recognition and normalization of temporal expressions in ...
The use of contextualised word embeddings allowed for a relevant performance increase for almost all...
This report describes the annotation guidelines for Italian of the TimeML specifications.Questo repo...
This paper presents ITA-Chronos, the system developed at FBK-irst to participate in the “Temporal E...
In this paper we describe the systems we used to participate in the task TAG-it of EVALITA 2020. The...