A word's sentiment depends on the domain in which it is used. Computational social science
research thus requires sentiment lexicons that are specific to the domains being studied. We …

We present a system for identifying the semantic relationships, or semantic roles, filled by
constituents of a sentence within a semantic frame. Given an input sentence and a target …

Subjectivity tagging is distinguishing sentences used to present opinions and evaluations
from sentences used to objectively present factual information. There are numerous …

This book is aimed at providing an overview of several aspects of semantic role labeling.
Chapter 1 begins with linguistic background on the definition of semantic roles and the …

This article shows that the Web can be employed to obtain frequencies for bigrams that are
unseen in a given corpus. We describe a method for retrieving counts for adjective-noun …

We present a novel approach to automatic metaphor identification in unrestricted text.
Starting from a small seed set of manually annotated metaphorical expressions, the system …

Metaphor is highly frequent in language, which makes its computational processing
indispensable for real-world NLP applications addressing semantic tasks. Previous …

This article presents clustering experiments on German verbs: A statistical grammar model
for German serves as the source for a distributional verb description at the lexical syntax …

Estimating word co-occurrence probabilities is a problem underlying many applications in
statistical natural language processing. Distance-weighted (or similarityweighted) averaging …

Techniques that exploit knowledge of distributional similarity between words have been
proposed in many areas of Natural Language Processing. For example, in language …