Articles

Most work on unsupervised entailment rule acquisition focused on rules between templates with two variables, ignoring unary rules - entailment rules between templates with a single variable. In this pa- per we investigate two approaches for un- supervised learning of such rules and com- pare the proposed methods with a …...

In Semantic Role Labeling (SRL), argu- ments are usually limited in a syntax sub- tree. It is reasonable to label arguments lo- cally in such a sub-tree rather than a whole tree. To identify active region of argu- ments, this paper models Maximal Pro- jection (MP), which is a concept …...

We determine the subjectivity of word senses. To avoid costly annotation, we evaluate how useful existing resources es- tablished in opinion mining are for this task. We show that results achieved with existing resources that are not tailored to- wards word sense subjectivity classifica- tion can rival results achieved with …...

Within the area of general-purpose fine- grained subjectivity analysis, opinion topic identification has, to date, received little attention due to both the difficulty of the task and the lack of appropriately anno- tated resources. In this paper, we pro- vide an operational definition of opinion topic and present an algorithm …...

Supervised approaches to Word Sense Dis- ambiguation (WSD) have been shown to outperform other approaches but are ham- pered by reliance on labeled training ex- amples (the data acquisition bottleneck). This paper presents a novel approach to the automatic acquisition of labeled examples for WSD which makes use of the …...

This work proposes opinion frames as a representation of discourse-level associa- tions which arise from related opinion top- ics. We illustrate how opinion frames help gather more information and also assist disambiguation. Finally we present the re- sults of our experiments to detect these as- sociations. 1...

The distance or similarity metric plays an important role in many natural language processing (NLP) tasks. Previous stud- ies have demonstrated the effectiveness of a number of metrics such as the Jaccard coefficient, especially in synonym acqui- sition. While the existing metrics per- form quite well, to further improve perfor- …...

Psycholinguistic studies suggest a model of human language processing that 1) per- forms incremental interpretation of spo- ken utterances or written text, 2) preserves ambiguity by maintaining competing anal- yses in parallel, and 3) operates within a severely constrained short-term memory store — possibly constrained to as few as four …...

This paper presents a probabilistic model for Japanese zero anaphora resolution. First, this model recognizes discourse en- tities and links all mentions to them. Zero pronouns are then detected by case struc- ture analysis based on automatically con- structed case frames. Their appropriate antecedents are selected from the entities with …...

We present a HMM part-of-speech tag- ging method which is particularly suited for POS tagsets with a large number of fine-grained tags. It is based on three ideas: (1) splitting of the POS tags into attribute vectors and decomposition of the contex- tual POS probabilities of the HMM into a …...

This paper describes the supervised ac- quisition of semantic event frames based on a corpus of biomedical abstracts, in which the biological process of E. coli gene regulation has been linguistically annotated by a group of biologists in the EC research project "BOOTStrep". Gene regulation is one of the rapidly …...

 Most data-driven dependency parsing approaches assume that sentence struc- ture is represented as trees. Although trees have several desirable properties from both computational and linguistic perspectives, the structure of linguistic phenomena that goes beyond shallow syntax often cannot be fully captured by tree representations. We present a pars- ing …...

In this paper, we consider classifying word positions by whether or not they can either start or end multi-word constituents. This provides a mechanism for “closing” chart cells during context-free inference, which is demonstrated to improve efficiency and accuracy when used to constrain the well- known Charniak parser. Additionally, we …...

The WordNet verb hierarchy is tested, with a view to improving the perform- ance of its applications, revealing topo- logical anomalies and casting doubt on its semantic categories. Encoded tro- ponyms frequently misrepresent other kinds of entailment. Approaches are pro- posed for correcting these anomalies in- cluding a new top …...

We introduce a novel semantic represen- tation formalism, Almost Flat Functional semantics (AFF), which is designed as an intelligent compromise between linguis- tically motivated predicate/argument se- mantics and ad hoc engineering solutions based on flat feature/value lists; the cen- tral idea is to tag each semantic element with the functional …...

This paper proposes a method for auto- matic POS (part-of-speech) guessing of Chinese unknown words. It contains two models. The first model uses a machine- learning method to predict the POS of unknown words based on their internal component features. The credibility of the results of the first model is …...

This paper proposes a new approach to dynamically determine the tree span for tree kernel-based semantic relation ex- traction. It exploits constituent dependen- cies to keep the nodes and their head children along the path connecting the two entities, while removing the noisy in- formation from the syntactic parse tree, …...

Quickly moving to a new area of research is painful for researchers due to the vast amount of scientific literature in each field of study. One possible way to overcome this problem is to summarize a scientific topic. In this paper, we propose a model of summarizing a single article, …...

User logs of search engines have recently been applied successfully to improve var- ious aspects of web search quality. In this paper, we will apply pairs of user queries and snippets of clicked results to train a machine translation model to bridge the “lexical gap” between query and document space. …...

We present an algorithm for unsupervised induction of labeled parse trees. The al- gorithm has three stages: bracketing, ini- tial labeling, and label clustering. Brack- eting is done from raw text using an un- supervised incremental parser. Initial la- beling is done using a merging model that aims at minimizing …...