Year: 2010
Type: conference-paper
Abstract: 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.
Source: Apollo (University of Cambridge)
DOI: 10.17863/cam.13157
Authors: Rei, M, Briscoe, T
Institution: University of Cambridge
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W62684482