Slim Epistemology with a Thick Skin

The distinction between ‘thick’ and ‘thin’ value concepts, and its importance to ethical theory, has been an active topic in recent meta-ethics. This paper defends three claims regarding the parallel issue about thick and thin epistemic concepts. (1) Analogy with ethics offers no straightforward way to establish a good, clear distinction between thick and thin epistemic concepts. (2) Assuming there is such a distinction, there are no semantic grounds for assigning thick epistemic concepts priority over the thin. (3) Nor does the structure of substantive epistemological theory establish that thick epistemic concepts enjoy systematic theoretical priority over the thin. In sum, a good case has yet to be made for any radical theoretical turn to thicker epistemology

Slim Epistemology with a Thick Skin

The distinction between “thick” and “thin” value concepts, and its importance to ethical theory, has been an active topic in recent meta-ethics. This paper defends three claims regarding the parallel issue about thick and thin epistemic concepts. (1) Analogy with ethics offers no straightforward way to establish a good, clear distinction between thick and thin epistemic concepts. (2) Assuming there is such a distinction, there are no semantic grounds for assigning thick epistemic concepts priority over the thin. (3) Nor does the structure of substantive epistemological theory establish that thick epistemic concepts enjoy systematic theoretical priority over the thin. In sum, a good case has yet to be made for any radical theoretical turn to thicker epistemology

Detecting and ordering adjectival scalemates

This paper presents a pattern-based method that can be used to infer adjectival scales, such as , from a corpus. Specifically, the proposed method uses lexical patterns to automatically identify and order pairs of scalemates, followed by a filtering phase in which unrelated pairs are discarded. For the filtering phase, several different similarity measures are implemented and compared. The model presented in this paper is evaluated using the current standard, along with a novel evaluation set, and shown to be at least as good as the current state-of-the-art.Comment: Paper presented at MAPLEX 2015, February 9-10, Yamagata, Japan (http://lang.cs.tut.ac.jp/maplex2015/

A CCG-based Compositional Semantics and Inference System for Comparatives

Comparative constructions play an important role in natural language inference. However, attempts to study semantic representations and logical inferences for comparatives from the computational perspective are not well developed, due to the complexity of their syntactic structures and inference patterns. In this study, using a framework based on Combinatory Categorial Grammar (CCG), we present a compositional semantics that maps various comparative constructions in English to semantic representations and introduces an inference system that effectively handles logical inference with comparatives, including those involving numeral adjectives, antonyms, and quantification. We evaluate the performance of our system on the FraCaS test suite and show that the system can handle a variety of complex logical inferences with comparatives.Comment: 10 pages, to appear in the Proceedings of PACLIC3

Extracting Scales of Measurement Automatically from Biomedical Text with Special Emphasis on Comparative and Superlative Scales

Abstract In this thesis, the focus is on the topic of “Extracting Scales of Measurement Automatically from Biomedical Text with Special Emphasis on Comparative and Superlative Scales.” Comparison sentences, when considered as a critical part of scales of measurement, play a highly significant role in the process of gathering information from a large number of biomedical research papers. A comparison sentence is defined as any sentence that contains two or more entities that are being compared. This thesis discusses several different types of comparison sentences such as gradable comparisons and non-gradable comparisons. The main goal is extracting comparison sentences automatically from the full text of biomedical articles. Therefore, the thesis presents a Java program that could be used to analyze biomedical text to identify comparison sentences by matching the sentences in the text to 37 syntactic and semantic features. These features or qualities would be helpful to extract comparative sentences from any biomedical text. Two machine learning techniques are used with the 37 roles to assess the curated dataset. The results of this study are compared with earlier studies

Semantic profiles of antonymic adjectives in discourse

This study has two goals: Firstly, to give an account of the semantic organization of individually used antonymic adjectives in discourse, and secondly, based on these finding, and previous work on antonymic meanings, contribute to a comprehensive theoretical account of their representation within the framework of Cognitive Linguistics. The hypothesis is that the members of the pairs are used in the same contexts and in the same type of constructions, not only when they co-occur and are used to express binary opposition as shown in previous work, but also otherwise. The manually coded corpus data from the BNC are analyzed along four semantic parameters: (i) the configuration of the adjectives in terms of gradability, (ii) the way they modify the nominal meanings, i.e. attributively or predicatively (iii) the meaning type of the modified nouns, and (iv) the status of the constructions with respect to whether their meanings are what we refer to as ‘basic’, metaphorical or metonymical. Multi-dimensional correspondence analysis technique is used to identify similarity spaces on the basis of the totality of the data. As predicted, our findings confirm a high degree of pairwise similarity – and some differences. On the basis of these results, it can be argued that the long-standing controversy within Structuralism between proponents of the co-occurrence hypothesis and the substitutability hypothesis in antonym research is a non-issue