Multi-class Animacy Classification with Semantic Features

نویسنده

  • Johannes Bjerva
چکیده

Animacy is the semantic property of nouns denoting whether an entity can act, or is perceived as acting, of its own will. This property is marked grammatically in various languages, albeit rarely in English. It has recently been highlighted as a relevant property for NLP applications such as parsing and anaphora resolution. In order for animacy to be used in conjunction with other semantic features for such applications, appropriate data is necessary. However, the few corpora which do contain animacy annotation, rarely contain much other semantic information. The addition of such an annotation layer to a corpus already containing deep semantic annotation should therefore be of particular interest. The work presented in this paper contains three main contributions. Firstly, we improve upon the state of the art in multiclass animacy classification. Secondly, we use this classifier to contribute to the annotation of an openly available corpus containing deep semantic annotation. Finally, we provide source code, as well as trained models and scripts needed to reproduce the results presented in this paper, or aid in annotation of other texts.1

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Exploring the distribution of animacy: experiments on Norwegian

Animacy is a an inherent property of the referents of nouns which has been claimed to figure as an influencing factor in a range of different grammatical phenomena in various languages. In recent years several linguistic studies have examined the influence of argument animacy in grammatical phenomena such as differential object marking (Aissen, 2003), the passive construction (Dingare, 2001), t...

متن کامل

Feature-based Malicious URL and Attack Type Detection Using Multi-class Classification

Nowadays, malicious URLs are the common threat to the businesses, social networks, net-banking etc. Existing approaches have focused on binary detection i.e. either the URL is malicious or benign. Very few literature is found which focused on the detection of malicious URLs and their attack types. Hence, it becomes necessary to know the attack type and adopt an effective countermeasure. This pa...

متن کامل

Semantic annotation of French corpora: animacy and verb semantic classes

This paper presents a first corpus of French annotated for animacy and for verb semantic classes. The resource consists of 1,346 sentences extracted from three different corpora: the French Treebank (Abeillé and Barrier, 2004), the Est-Républicain corpus (CNRTL) and the ESTER corpus (ELRA). It is a set of parsed sentences, containing a verbal head subcategorizing two complements, with annotatio...

متن کامل

Identification of Houseplants Using Neuro-vision Based Multi-stage Classification System

In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...

متن کامل

MLIFT: Enhancing Multi-label Classifier with Ensemble Feature Selection

Multi-label classification has gained significant attention during recent years, due to the increasing number of modern applications associated with multi-label data. Despite its short life, different approaches have been presented to solve the task of multi-label classification. LIFT is a multi-label classifier which utilizes a new strategy to multi-label learning by leveraging label-specific ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014