Articles

We present a system for the semantic role la- beling task. The system combines a machine learning technique with an inference procedure based on integer linear programming that sup- ports the incorporation of linguistic and struc- tural constraints into the decision process. The system is tested on the data provided …...

Compound terms play a surprisingly key role in the organization of lexical ontologies. However, their inclusion forces one to address the issues of completeness and consistency that naturally arise from this organizational role. In this paper we show how creative exploration in the space of literal compounds can reveal not …...

Precise Natural Language Understanding is needed in Geometry Tutoring to accurately determine the semantic content of students’ explanations. The paper presents an NLU system developed in the context of the Geometry Explanation Tutor. The system combines unification-based syntactic processing with description logics based semantics to achieve the necessary accuracy level. …...

Lexico-semantic networks such as WordNet have been criticized about the nature of the senses they distinguish as well as on the way they define these senses. In this article, we pre- sent a possible solution to overcome these lim- its by defining the sense of words from the way they …...

In this paper we describe the extraction of thesaurus information from parsed dictio- nary definition sentences. The main data for our experiments comes from Lexeed, a Japanese semantic dictionary, and the Hinoki treebank built on it. The dictio- nary is parsed using a head-driven phrase structure grammar of Japanese. Knowledge …...

The paper presents a method for word sense disambiguation based on parallel corpora. The method exploits recent advances in word alignment and word clustering based on automatic extraction of translation equivalents and being supported by available aligned wordnets for the languages in the corpus. The wordnets are aligned to the …...

In this paper, we introduce a new semi-supervised learning model for word sense disambiguation based on Kernel Prin- cipal Component Analysis (KPCA), with experiments showing that it can further improve accuracy over supervised KPCA models that have achieved WSD accuracy superior to the best published individual models. Although empirical results …...

We present an automatic approach to learn- ing criteria for classifying the parts-of-speech used in lexical mappings. This will fur- ther automate our knowledge acquisition sys- tem for non-technical users. The criteria for the speech parts are based on the types of the denoted terms along with morphological and corpus-based …...

In this paper we describe the analytic question answering system HITIQA (High- Quality Interactive Question Answering) which has been developed over the last 2 years as an advanced research tool for information analysts. HITIQA is an interactive open- domain question answering technology designed to allow analysts to pose complex exploratory …...

We investigate the impact of the precision/recall trade-off of information extraction on the per- formance of an offline corpus-based question answering (QA) system. One of our findings is that, because of the robust final answer selection mechanism of the QA system, recall is more im- portant. We show that the …...

While research on question answering has be- come popular in recent years, the problem of ef- ficiently locating a complete set of distinct answers to list questions in huge corpora or the Web is still far from being solved. This paper ex- ploits the wealth of freely available text and …...

We present a constraint-based syntax-semantics interface for the construction of RMRS (Robust Minimal Recursion Semantics) representations from shallow grammars. The architecture is de- signed to allow modular interfaces to existing shallow grammars of various depth – ranging from chunk grammars to context-free stochastic grammars. We define modular semantics con- struction …...

We use the interpretation of vague scalar predi- cates like small as an illustration of how system- atic semantic models of dialogue context en- able the derivation of useful, fine-grained utter- ance interpretations from radically underspeci- fied semantic forms. Because dialogue context suffices to determine salient alternative scales and relevant …...

The Colorado Literacy Tutor (CLT) is a technology-based literacy program, designed on the basis of cognitive theory and scientifically motivated reading research, which aims to improve literacy and student achievement in public schools. One of the critical components of the CLT is a speech recognition system which is used to …...

This paper shows how to construct semantic representations from the derivations produced by a wide-coverage CCG parser. Unlike the de- pendency structures returned by the parser it- self, these can be used directly for semantic in- terpretation. We demonstrate that well-formed semantic representations can be produced for over 97% of …...

As part of its description of lexico-semantic predicate frames or conceptual structures, the FrameNet project defines a set of semantic roles specific to the core predicate of a sentence. Recently, researchers have tried to automatically produce semantic interpretations of sentences using this information. Building on prior work, we describe a …...

In this paper, a novel semantic role labeler based on dependency trees is developed. This is ac- complished by formulating the semantic role la- beling as a classification problem of dependency relations into one of several semantic roles. A dependency tree is created from a constituency parse of an input …...

In this paper we show that an unsupervised method for ranking word senses automatically can be used to iden- tify infrequently occurring senses. We demonstrate this using a ranking of noun senses derived from the BNC and evaluating on the sense-tagged text available in both SemCor and the SENSEVAL-2 English …...

This paper presents a method to construct Japanese KATAKANA variant list from large corpus. Our method is useful for information retrieval, information extrac- tion, question answering, and so on, because KATAKANA words tend to be used as “loan words” and the transliteration causes several variations of spelling. Our method consists …...

Word segmentation is an important part of many applications, including information retrieval, information filtering, document analysis, and text summarization. In Thai language, the process is complicated since words are written continuously, and their structures are not well-defined. A recognized effective approach to word segmentation is Longest Matching, a method based …...