Assessing the contribution of shallow and deep knowledge sources for word sense disambiguation

Corpus-based techniques have proved to be very beneficial in the development of efficient and accurate approaches to word sense disambiguation (WSD) despite the fact that they generally represent relatively shallow knowledge. It has always been thought, however, that WSD could also benefit from deeper knowledge sources. We describe a novel approach to WSD using inductive logic programming to learn theories from first-order logic representations that allows corpus-based evidence to be combined with any kind of background knowledge. This approach has been shown to be effective over several disambiguation tasks using a combination of deep and shallow knowledge sources. Is it important to understand the contribution of the various knowledge sources used in such a system. This paper investigates the contribution of nine knowledge sources to the performance of the disambiguation models produced for the SemEval-2007 English lexical sample task. The outcome of this analysis will assist future work on WSD in concentrating on the most useful knowledge sources

Chomskyan Arguments Against Truth-Conditional Semantics Based on Variability and Co-predication

In this paper I try to show that semantics can explain word-to-world relations and that sentences can have meanings that determine truth-conditions. Critics like Chomsky typically maintain that only speakers denote, i.e., only speakers, by using words in one way or another, represent entities or events in the world. However, according to their view, individual acts of denotations are not explained just by virtue of speakers’ semantic knowledge. Against this view, I will hold that, in the typical cases considered, semantic knowledge can account for the denotational uses of words of individual speakers

Using NLP meta, Milton, metaphor models, for improving the activity of the organization

The objective of this paper is the improving of the three methods from the neuro- linguistic programming – metaphor, Milton model and the meta-model, so by using this in daily activities by an organization to improve the activities witch, are performed and to have a more efficient allocation of the available resources.neuro linguistic programming (NLP), metaphor, Milton model, meta-model.

On the path of time: Temporal motion in typological perspective

The Moving Ego and Moving Time metaphors have provided a fertile testing ground for the psychological reality of space–time metaphors. Despite this, little research has targeted the linguistic patterns used in these two mappings. To fill that gap, the current study uses corpus data to examine the use of motion verbs in two typologically different languages, English and Spanish. We first investigated the relative frequency of the two metaphors. Whereas we observed no difference in frequency in the Spanish data, our findings indicated that in English, Moving Time expressions are more prevalent than are Moving Ego expressions. Second, we focused on the patterns of use of the verbs themselves, asking whether well-known typological patterns in the expression of spatial motion would carry over to temporal motion. Specifically, we examined the frequencies of temporal uses of path and manner verbs in English and in Spanish. Contra the patterns observed in space, we observed a preference for path verbs in both languages, with this preference more strongly evident in English than in Spanish. In addition, our findings revealed greater use of motion verbs in temporal expressions in Spanish compared to English. These findings begin to outline constraints on the aspects of spatial conceptualization that are likely to be reused in the conceptualization of time

A Dataset for Movie Description

Descriptive video service (DVS) provides linguistic descriptions of movies and allows visually impaired people to follow a movie along with their peers. Such descriptions are by design mainly visual and thus naturally form an interesting data source for computer vision and computational linguistics. In this work we propose a novel dataset which contains transcribed DVS, which is temporally aligned to full length HD movies. In addition we also collected the aligned movie scripts which have been used in prior work and compare the two different sources of descriptions. In total the Movie Description dataset contains a parallel corpus of over 54,000 sentences and video snippets from 72 HD movies. We characterize the dataset by benchmarking different approaches for generating video descriptions. Comparing DVS to scripts, we find that DVS is far more visual and describes precisely what is shown rather than what should happen according to the scripts created prior to movie production

On the Proper Domain of Psychological Predicates

One question of the bounds of cognition is that of which things have it. A scientifically relevant debate on this question must explain the persistent and selective use of psychological predicates to report findings throughout biology: for example, that neurons prefer, fruit flies and plants decide, and bacteria communicate linguistically. This paper argues that these claims should enjoy default literal interpretation. An epistemic consequence is that these findings can contribute directly to understanding the nature of psychological capacities