University of Cambridge > Talks.cam > NLIP Seminar Series > Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection

Download to your calendar using vCal

If you have a question about this talk, please contact Laura Rimell .

Hedge cues were detected using a supervised Conditional Random Field (CRF) classifier exploiting features from the RASP parser. The CRF ’s predictions were filtered using known cues and unseen instances were removed, increasing precision while retaining recall. Rules for scope detection, based on the grammatical relations of the sentence and the part-of-speech tag of the cue, were manually developed. However, another supervised CRF classifier was used to refine these predictions. As a final step, scopes were constructed from the classifier output using a small set of post-processing rules. Development of the system revealed a number of issues with the annotation scheme adopted by the organisers.

Joint work with Ted Briscoe.

This talk is part of the NLIP Seminar Series series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Wolfson room, Lucy Cavendish college Average on Sundays: 7387.82608696 kWh Work or Play? Inside an entrepreneurial journey

Other talks

Discussion I Non-stationarity in structural dynamics, challenges and implications for modelling and structural health monitoring External Seminar - Jenn Brophy TBC Title to be confirmed Cambridge Reading Group on Reproduction: Professor Sara Brill Group Presentation 5
 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity