Learn More
This paper presents SemFrame, a system that induces frame semantic verb classes from WordNet and LDOCE. Semantic frames are thought to have significant potential in resolving the paraphrase problem challenging many language-based applications. When compared to the handcrafted FrameNet, SemFrame achieves its best recall-precision balance with 83.2% recall(More)
The IAMTC project (Interlingual Annotation of Multilingual Translation Corpora) is developing an interlingual representation framework for annotation of parallel corpora (English paired with Arabic, French, Hindi, Japanese, Korean, and Spanish) with deep-semantic representations. In particular, we are investigating meaning equivalent paraphrases involving(More)
This paper explores factors correlating with lack of inter-annotator agreement on a word sense dis-ambiguation (WSD) task taken from SENSEVAL-2. Twenty-seven subjects were given a series of tasks requiring word sense judgments. Subjects were asked to judge the applicability of word senses to polyse-mous words used in context. Metrics of lexical ability were(More)
This paper focuses on an important step in the creation of a system of meaning representation and the development of semantically annotated parallel corpora, for use in applications such as machine translation, question answering, text summarization, and information retrieval. The work described below constitutes the first effort of any kind to annotate(More)
This paper describes automatic techniques for mapping 9611 entries in a database of English verbs to WordNet senses. The verbs were initially grouped into 491 classes based on syntactic categories. Mapping these classiied verbs into WordNet senses provides a resource that may be used for disambiguation in multilingual applications such as machine(More)