Abstract
This paper describes two experiments: one exploring the amount of information relevant to sense disambiguation contained in the part-of-speech field of entries in a Machine Readable Dictionary (MRD); the other, more practical, experiment attempts sense disambiguation of all content words in a text assigning MRD homographs as sense tags using only part-of-speech information. We have implemented a simple sense tagger which successfully tags 94% of words using this method. A plan to extend this work and implement an improved sense tagger is included.
Keywords
Affiliated Institutions
Related Publications
Word Space
Representations for semantic information about words are necessary for many applications of neural networks in natural language processing. This paper describes an efficient, co...
A decision tree of bigrams is an accurate predictor of word sense
This paper presents a corpus-based approach to word sense disambiguation where a decision tree assigns a sense to an ambiguous word based on the bigrams that occur nearby. This ...
Feature-rich part-of-speech tagging with a cyclic dependency network
We present a new part-of-speech tagger that demonstrates the following ideas: (i) explicit use of both preceding and following tag contexts via a dependency network representati...
A unified architecture for natural language processing
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named enti...
Mining WordNet for a Fuzzy Sentiment: Sentiment Tag Extraction from WordNet Glosses
Many of the tasks required for semantic tagging of phrases and texts rely on a list of words annotated with some semantic features. We present a method for extracting sentiment-...
Publication Info
- Year
- 1998
- Type
- article
- Volume
- 4
- Issue
- 2
- Pages
- 135-143
- Citations
- 87
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1017/s1351324998001946