Formal semantics has traditionally distinguished between extensional and intensional aspects of meaning, roughly equivalent to reference and what people intuitively call "meaning", respectively. It has primarily focused on extension, since this allows for predictions to be made and tested by building models of meaning that are directly grounded on reference, using set theoretic tools. Distribut...

This paper applies machine learning techniques to acquiring aspects of the meaning of discourse markers. Three subtasks of acquiring the meaning of a discourse marker are considered: learning its polarity, veridicality, and type (i.e. causal, temporal or additive). Accuracy of over 90% is achieved for all three tasks, well above the baselines.

We suggest that the primary motivation for an agent to construct a symbol-meaning mapping is to solve a task. The meaning space of an agent should be derived from the tasks that it faces during the course of its lifetime. We outline a process in which agents learn to solve multiple tasks and extract a store of “cumulative knowledge” that helps them to solve each new task more quickly and accura...

A distributed representation has become a popular approach to capturing a word meaning. Besides its success and practical value, however, questions arise about the relationships between a true word meaning and its distributed representation. In this paper, we examine such a relationship via polymodal embedding approach inspired by the theory that humans tend to use diverse sources in developing...

Background: Finding the right word is a necessity in communication, and its evaluation has always been a challenging clinical issue, suggesting the need for valid and reliable measurements. The Homophone Meaning Generation Test (HMGT) can measure the ability to switch between verbal concepts, which is required in word retrieval. The purpose of this study was to adapt and validate the Persian ve...

Ramon Ziai1, Niels Ott1, Detmar Meurers2 1Sonderforschungsbereich 833, 2Seminar für Sprachwissenschaft, Universität Tübingen . .Research Questions . • What linguistic representations can be used robustly and efficiently in an automatic meaning comparison? • What is the role of context and how can we utilize knowledge about it in comparing meaning automatically? Context heremeans questions and r...

We propose in this paper a greedy method to the problem of measuring semantic similarity between short texts. Our method is based on the principle of compositionality which states that the overall meaning of a sentence can be captured by summing up the meaning of its parts, i.e. the meanings of words in our case. Based on this principle, we extend wordto-word semantic similarity metrics to quan...

Practical tasks like question answering and machine translational ultimately require computing meaning representations that support inference. Standard linguistic accounts of meaning are impracticable for such purposes, both because they assume nonmonotonic operations such as quantifier movement, and because they lack a representation for the meaning of content words that supports efficient com...

This study aimed to investigate the relative effectiveness of consciousness-raising tasks and structure-based production tasks in comparison with the traditional teaching in learning comparative and superlative forms, following a task-based approach to teaching English grammar. To this end, from among 82 female elementary-level high school students having taken a Solutions Placement Test (2010)...

: This study aims to apply active learning in a foreign language context to improve L2 learners’ listening comprehension. Participants in this attempt were 56 EFL learners between 13 and 15 years old. To amass the required data, learners went through a ten-week treatment, in which participants in the experimental group received computer-mediated active learning intervention and...