This paper presents the design and results of a crowdsourcing experiment on the recognition of Italian event nominals. The aim of the experiment was to assess the feasibility of crowdsourcing methods for a complex semantic task such as distinguishing the eventive interpretation of polysemous nominals taking into consideration various types of syntagmatic cues. Details on the theoretical background and on the experiment set up are provided together with the final results in terms of accuracy and inter-annotator agreement. These results are compared with the ones obtained by expert annotators on the same task. The low values in accuracy and Fleiss’ kappa of the crowdsourcing experiment demonstrate that crowdsourcing is not always optimal for ...
We describe the acquisition, based on crowdsourcing, of opposition relations among Italian verb sens...
We develop an NLP method for inferring potential contributors among multitude of users within crowds...
We develop an NLP method for inferring potential contributors among multitude of users within crowds...
This paper presents the design and results of a crowdsourcing experiment on the recognition of Itali...
This paper presents the design and results of a crowdsourcing experiment on the recognition of Itali...
This paper presents the design and results of a crowdsourcing experiment on the recognition of Itali...
This paper describes two sets of crowdsourcing experiments on temporal information annotation conduc...
This paper describes two sets of crowdsourcing experiments on temporal information annotation conduc...
This paper describes two sets of crowdsourcing experiments on temporal information annotation conduc...
This paper reports on two crowdsourcing experiments on Temporal Relation Annotation in Italian and E...
© 2017 Dr. Richard James FothergillWords can take on many meanings, and collecting and identifying e...
We describe an experiment for the acquisition of opposition relations among Italian verb senses, bas...
In this paper, we present a new dataset of semantically related Italian word pairs. The dataset co...
In this paper, we present a new dataset of semantically related Italian word pairs. The dataset co...
In this paper, we present a new dataset of semantically related Italian word pairs. The dataset co...
We describe the acquisition, based on crowdsourcing, of opposition relations among Italian verb sens...
We develop an NLP method for inferring potential contributors among multitude of users within crowds...
We develop an NLP method for inferring potential contributors among multitude of users within crowds...
This paper presents the design and results of a crowdsourcing experiment on the recognition of Itali...
This paper presents the design and results of a crowdsourcing experiment on the recognition of Itali...
This paper presents the design and results of a crowdsourcing experiment on the recognition of Itali...
This paper describes two sets of crowdsourcing experiments on temporal information annotation conduc...
This paper describes two sets of crowdsourcing experiments on temporal information annotation conduc...
This paper describes two sets of crowdsourcing experiments on temporal information annotation conduc...
This paper reports on two crowdsourcing experiments on Temporal Relation Annotation in Italian and E...
© 2017 Dr. Richard James FothergillWords can take on many meanings, and collecting and identifying e...
We describe an experiment for the acquisition of opposition relations among Italian verb senses, bas...
In this paper, we present a new dataset of semantically related Italian word pairs. The dataset co...
In this paper, we present a new dataset of semantically related Italian word pairs. The dataset co...
In this paper, we present a new dataset of semantically related Italian word pairs. The dataset co...
We describe the acquisition, based on crowdsourcing, of opposition relations among Italian verb sens...
We develop an NLP method for inferring potential contributors among multitude of users within crowds...
We develop an NLP method for inferring potential contributors among multitude of users within crowds...