We show existence of equilibria in distributional strategies for a wide class of private value auctions, including the first general existence result for double auctions. The set of equilibria is invariant to the tie-breaking rule. The model incorporates multiple unit demands, all standard pricing rules, reserve prices, entry costs, and stochastic demand and supply. Valuations can be correlated...

This paper describes an application of distributional semantics to the study of syntactic productivity in diachrony, i.e., the property of grammatical constructions to attract new lexical items over time. By providing an empirical measure of semantic similarity between words derived from lexical co-occurrences, distributional semantics not only reliably captures how the verbs in the distributio...

In this study, we propose an approach to determine restrictions in adjective ordering through the use of compositional methods in distributional semantics. Specifically, we focus on being able to automatically distinguish phrases in which there is flexibility in the adjective ordering from those bound to a rigid order. We explore a number of measures extracted from the distributional representa...

This paper presents some observations on the syntax and semantics of the Tagalog phrase marking particles ang, ng, and sa. More specifically, it is concerned with investigating the following two points. First, while there is some evidence for the widely held view that the phase marking particles form a kind of paradigm in that they are at least in partial complementary distribution, they differ...

Research into corpus-based semantics has focused on the development of ad hoc models that treat single tasks, or sets of closely related tasks, as unrelated challenges to be tackled by extracting different kinds of distributional information from the corpus. As an alternative to this “one task, one model” approach, the Distributional Memory framework extracts distributional information once and...

Recognising the grammatical categories of words is a necessary skill for the acquisition of syntax and for on-line sentence processing. The syntactic and semantic context of the word contribute as cues for grammatical category assignment, but phonological cues, too, have been implicated as important sources of information. The value of phonological and distributional cues has not, with very few...

Most attempts to integrate FrameNet in NLP systems have so far failed because of its limited coverage. In this paper, we investigate the applicability of distributional and WordNetbased models on the task of lexical unit induction, i.e. the expansion of FrameNet with new lexical units. Experimental results show that our distributional and WordNet-based models achieve good level of accuracy and ...

The use of distributional semantics to represent the meaning of a single word has proven to be very effective, but there still is difficulty representing the meaning of larger constituents, such as a noun phrase. In general, it is unclear how to find a representation of phrases that preserves syntactic distinctions and the relationship between a compound’s constituents. This paper is an attempt...

In this paper, we present a model of statistical word-level mapping for comparable corpora. The approach is based on the assumption that if two terms have close distributional profiles, their corresponding translations’ distributional profiles should be close in a comparable corpus. The proposed model is described. A preliminary investigation on intralanguage comparable corpora is laid out. The...

In this position paper we argue that an adequate semantic model must account for language in use, taking into account how discourse context affects the meaning of words and larger linguistic units. Distributional semantic models are very attractive models of meaning mainly because they capture conceptual aspects and are automatically induced from natural language data. However, they need to be ...