A new almost-parsing language model incorporating multiple knowledge sources that is based upon the concept of Constraint Dependency Grammars is presented in this paper. Lexical features and syntactic constraints are tightly integrated into a uniform linguistic structure called a SuperARV that is associated with a word in the lexicon. The SuperARV language model reduces perplexity and word erro...

Second Language Information Transfer in Automatic Verb Classification – A Preliminary Investigation Vivian Tsang Master of Science Graduate Department of Computer Science University of Toronto 2001 Lexical semantic classes incorporate both syntactic and semantic information about verbs. Lexical semantic classification of verbs provide a great deal of useful information about the possible usage ...

Syntactic databases are increasingly available and are put to a variety of uses, including serving as organized reference material for descriptive and theoretical syntacticians. Dense databases recording fine variation within a single language area, so-called “microvariation”, play a prominent role with respect to this use. In addition the large collections allow syntactic variation to be studi...

Question answering (QA) systems provide an intuitive way of requesting concise information from a given data source. An important stage of such a system is the passage ranking stage, which ranks the possible answers based on their relevance to the question. There has been a lot of previous work on passage ranking, employing lexical, semantic or syntactic methods, but to our knowledge there has ...

We present an approach for Semantic Role Labeling (SRL) using Conditional Random Fields in a joint identification/classification step. The approach is based on shallow syntactic information (chunks) and a number of lexicalized features such as selectional preferences and automatically inferred similar words, extracted using lexical databases and distributional similarity metrics. We use semanti...

In Chinese, nouns need numeral classifiers to express quantity. In this paper, we explore the relationship between classifiers and nouns. We extract a set of lexical, syntactic and ontological features and the corresponding noun-classifier pairs from a corpus and then train SVMs to assign classifers to nouns. We analyse which features are most important for this task.

Paraphrasing refers to conveying the same content in several ways. The successful recognition of paraphrases is crucial to various natural language processing tasks such as Information Extraction, Document Summarization, Question Answering etc. Several techniques have been employed for paraphrase recognition using lexical, syntactic and semantic features. Many of these systems have been tested ...

Textual entailment has been proposed as a unifying generic framework for modeling language variability and semantic inference in different Natural Language Processing (NLP) tasks. This paper presents a novel statistical method for recognizing Chinese textual entailment in which lexical, syntactic with semantic matching features are combined together. In order to solve the problems of syntactic ...

We investigate the problem of readability assessment using a range of lexical and syntactic features and study their impact on predicting the grade level of texts. As empirical basis, we combined two web-based text sources, Weekly Reader and BBC Bitesize, targeting different age groups, to cover a broad range of school grades. On the conceptual side, we explore the use of lexical and syntactic ...

In this paper we outline a new architecture for modeling the interaction between syntax and prosody. This architecture does not make use of correspondences between separate projections, but it is still consonant with the overall framework of LFG. We propose that prosodic information is developed in a component that operates independently of the syntax, thus allowing easy description of misalign...