Interpretation of Nominal Compounds: Combining Domain-Independent and Domain-Specific Information
نویسنده
چکیده
A domain independent model is proposed for the automated interpretation of nominal compounds in English. This model is meant to account for productive rules of interpretation which are inferred from the morpho-syntact ic and semantic characteristics of the nominal constituents. In particular, we make extensive use of Pustejovsky's principles concerning the predicative information associated with nominals. We argue that it is necessary to draw a line between generalizable semantic principles and domainspecific semantic information. We explain this distinction and we show how this model may be applied to the interpretat ion of compounds in real texts, provided that complementary semantic information are retrieved.
منابع مشابه
Hybrid Approach for the Interpretation of Nominal Compounds using Ontology
Understanding and interpretation of nominal compounds has been a long-standing area of interest in NLP research for various reasons. (1) Nominal compounds occur frequently in most languages. (2) Compounding is an extremely productive word formation phenomenon. (3) Compounds contain implicit semantic relations between their constituent nouns. Most approaches that have been proposed so far concen...
متن کاملAn Ontology-Based Method for Extracting and Classifying Domain-Specific Compositional Nominal Compounds
In this paper, we present our preliminary study on an ontology-based method to extract and classify compositional nominal compounds in specific domains of knowledge. This method is based on the assumption that, applying a conceptual model to represent knowledge domain, it is possible to improve the extraction and classification of lexicon occurrences for that domain in a semi-automatic way. We ...
متن کاملPrediction of dispersed mineralization zone in depth using frequency domain of surface geochemical data
Discrimination of the blind and dispersed mineralization deposits is a challenging problem in geochemical exploration. The frequency domain (FD) of the surface geochemical data can solve this important issue. This new exploratory information can be achieved using the interpretation of FD of geochemical data, which is impossible in spatial domain. In this research work, FD of the surface geochem...
متن کاملDeep Unsupervised Domain Adaptation for Image Classification via Low Rank Representation Learning
Domain adaptation is a powerful technique given a wide amount of labeled data from similar attributes in different domains. In real-world applications, there is a huge number of data but almost more of them are unlabeled. It is effective in image classification where it is expensive and time-consuming to obtain adequate label data. We propose a novel method named DALRRL, which consists of deep ...
متن کاملCustomizing meaning: building domain-specific semantic representations from a generic lexicon
Language input to practical dialogue systems must be transformed into a semantic representation that is customized for use by the back-end domain reasoners. At the same time, we want to keep front-end system components as domain independent as possible for easy portability across multiple domains. We propose a transparent way to achieve domain specificity from a broad-coverage domain-independen...
متن کامل