1 / 11

Presenter : Cheng- Hui Chen Authors : Simone Paolo Ponzetto , Roberto Navigli ACL, 2010

Knowledge-rich Word Sense Disambiguation Rivaling Supervised Systems . Presenter : Cheng- Hui Chen Authors : Simone Paolo Ponzetto , Roberto Navigli ACL, 2010. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. WordNet. Motivation. Knowledge. Google.

jui
Télécharger la présentation

Presenter : Cheng- Hui Chen Authors : Simone Paolo Ponzetto , Roberto Navigli ACL, 2010

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Knowledge-rich Word Sense Disambiguation Rivaling Supervised Systems Presenter : Cheng-Hui ChenAuthors : Simone Paolo Ponzetto, Roberto NavigliACL, 2010

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments

  3. WordNet Motivation • Knowledge • Google • Wiki • One of the main obstacles to high-performance WSD is the knowledge acquisition bottleneck. ? • Other source WSD algorithm

  4. Objectives • To propose to automatically extend WordNet with large amounts of semantic relations from an encyclopedic resource, name Wikipedia. Knowledge WordNet Resource Wiki Resource WSD algorithm

  5. Framework WordNet resource 1.Synonymy 2.Hypernymy/Hyponymy 3.Sisterhood 4.Gloss Wiki resource 1.Sense labels 2.Links 3.Categories

  6. Methodology • Wiki • Sense labels • Links • Categories • WordNet • Synonymy • Hypernymy/Hyponymy • Sisterhood • Gloss

  7. Mapping algorithm • SODA (WordNet) • 1. namely the sodium carbonate • Salt, acetate,sodium, chlorate, benzoate • 2.the drink • Drink, soft, cola, bitter • Drink (Wiki) • Soft, drink, cola, sugar 1. 2. 0 2 9 9

  8. Experiments • Evaluation of the Mapping

  9. Experiments ExtLesk: I am super man Gloss, Sisterhood, Synonymy, Hypernumy/Hyponymy • Coarse-grained WSD

  10. Conclusions • This paper has presented a large-scale method for the automatic enrichment of a computational lexicon with encyclopedic relational knowledge. • The method enables simple knowledge-based WSD systems to perform as well as the highest-performing supervised system.

  11. Comments • Advantages • This paper uses the consistent example. • Applications • Knowledge-based WSD system.

More Related