Articles

This paper presents a large-scale evalua- tion of bag-of-words distributional models on two datasets from priming experiments involving syntagmatic and paradigmatic relations. We interpret the variation in performance achieved by different settings of the model parameters as an indication of which aspects of distributional patterns characterize these types of relations. …...

This paper describes a graphical semantic representation based on bottom-up ‘con- tinuation’ dependencies which has the im- portant property that its vertices define a usable set of discourse referents in work- ing memory even in contexts involving conjunction in the scope of quantifiers. An evaluation on an existing quantifier scope …...

With the advent of e-learning, there is a strong demand for tools that help to cre- ate e-learning courses in an automatic or semi-automatic way. While resources for new courses are often freely available, they are generally not properly structured into easy to handle units. In this paper, we investigate …...

We explore the novel task of identify- ing latent attributes in video scenes, such as the mental states of actors, using only large text collections as background knowledge and minimal information about the videos, such as activity and actor types. We formalize the task and a measure of merit that …...

This paper studies generation of descrip- tive sentences from densely annotated im- ages. Previous work studied generation from automatically detected visual infor- mation but produced a limited class of sen- tences, hindered by currently unreliable recognition of activities and attributes. In- stead, we collect human annotations of ob- jects, parts, …...

In this paper, we describe a computational model for motion events in natural lan- guage that maps from linguistic expres- sions, through a dynamic event interpreta- tion, into three-dimensional temporal sim- ulations in a model. Starting with the model from (Pustejovsky and Moszkow- icz, 2011), we analyze motion events us- …...

The field of compositional distributional semantics has proposed very interesting and reliable models for accounting the distributional meaning of simple phrases. These models however tend to disregard the syntactic structures when they are ap- plied to larger sentences. In this paper we propose the chunk-based smoothed tree kernels (CSTKs) as …...

This paper describes a series of French se- mantic role labelling experiments which show that a small set of manually anno- tated training data is superior to a much larger set containing semantic role labels which have been projected from a source language via word alignment. Using uni- versal part-of-speech …...

The aim of this paper is to discuss difficul- ties involved in adopting an existing sys- tem of semantic roles in a grammar engi- neering task. Two typical repertoires of se- mantic roles are considered, namely, Verb- Net and Sowa’s system. We report on ex- periments showing the low inter-annotator …...

Sentence Connectivity is a textual charac- teristic that may be incorporated intelli- gently for the selection of sentences of a well meaning summary. However, the ex- isting summarization methods do not uti- lize its potential fully. The present pa- per introduces a novel method for single- document text summarization. It …...

Human language allows us to express the same meaning in various ways. Recogniz- ing that the meaning of one text can be in- ferred from the meaning of another can be of help in many natural language process- ing applications. One such application is the categorization of emails. In this …...

We consider the task of automatically es- timating the value of human actions. We cast the problem as a supervised learning- to-rank problem between pairs of action descriptions. We present a large, novel data set for this task which consists of challenges from the I Will If You Will Earth …...

We describe a method of encoding cooc- currence information in a three-way tensor from which HAL-style word space mod- els can be derived. We use these models to identify semantic relations in a specialized corpus. Results suggest that the tensor- based methods we propose are more ro- bust than the …...

Explicit Semantic Analysis (ESA) is an ap- proach to calculate the semantic relatedness between two words or natural language texts with the help of concepts grounded in human cognition. ESA usage has received much at- tention in the field of natural language pro- cessing, information retrieval and text analy- sis, …...

We introduce an iterative approach to subgraph-based Word Sense Disambigua- tion (WSD). Inspired by the Sudoku puz- zle, it significantly improves the precision and recall of disambiguation. We describe how conventional subgraph-based WSD treats the two steps of (1) subgraph con- struction and (2) disambiguation via graph centrality measures as …...

In this paper, we investigate the differ- ence between word and sense similarity measures and present means to convert a state-of-the-art word similarity measure into a sense similarity measure. In or- der to evaluate the new measure, we cre- ate a special sense similarity dataset and re-rate an existing word …...

Research in emotion analysis of text sug- gest that emotion lexicon based features are superior to corpus based n-gram fea- tures. However the static nature of the general purpose emotion lexicons make them less suited to social media analysis, where the need to adopt to changes in vo- cabulary usage …...

This study explores the potential of us- ing deep semantic features to improve bi- nary sentiment classification of paragraph- length movie reviews from the IMBD website. Using a Naive Bayes classifier as a baseline, we show that features extracted from Minimal Recursion Semantics repre- sentations in conjunction with back-off re- …...

We present two Twitter datasets annotated with coarse-grained word senses (super- senses), as well as a series of experiments with three learning scenarios for super- sense tagging: weakly supervised learn- ing, as well as unsupervised and super- vised domain adaptation. We show that (a) off-the-shelf tools perform poorly on Twitter, …...

This paper presents a first, largely qualitative analysis of a set of human-human dialogues recorded specifically to provide insights in how humans handle pauses and resumptions in situations where the speakers cannot see each other, but have to rely on the acoustic signal alone. The work presented is part of …...