1 / 6

Anaphora Resolution

Anaphora Resolution. Sanghoon Kwak Takahiro Aoyama. Anaphora Resolution. Moussa said the presidents discussed the situation in Iraq and would return to it Monday. However, he would not comment on whether Syria and Egypt were planning to send planes to Baghdad.

serena
Télécharger la présentation

Anaphora Resolution

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. Anaphora Resolution Sanghoon Kwak Takahiro Aoyama

  2. Anaphora Resolution • Moussa said the presidents discussed the situation in Iraq and would return to it Monday. However, he would not comment on whether Syria and Egypt were planning to send planes to Baghdad. • Anaphora resolution is the process of determining whether a noun phrase refers to an antecedent noun phrase.

  3. Approach • Extracted 12 features for each noun phrase pair from a news article corpora • Constructed a training set using these 12 features. Used 70 news articles from NY Times and Broadcast News. • Built a decision tree with this training data using the C4.5 decision tree builder

  4. Features • Some of 12 features include… • Distance Distance by the number of sentences • Pronoun Whether a noun phrase is a pronoun or not • String match Whether two phrases have the same character sequence • Semantic Class Whether two phrases are in the same semantic class (Person, Organization, etc.) • Number Whether two phrases are both plural or both singular

  5. Result • Training and Test Result • Rules based on decision tree • DIST <= 0, JPRO = True, NUM = True, SEMCLASS = True •  Coreferent • IPRO = True, STR MATCH = true, DIST > 0 •  Not Coreferent

  6. Future Work • Train and test data from different domains (Blog posts, E-Mail messages, etc.) • Further subdivide decision tree classes

More Related