Analysing recall loss in named entity slot filling

6Citations
Citations of this article
88Readers
Mendeley users who have this article in their library.

Abstract

State-of-the-art fact extraction is heavily constrained by recall, as demonstrated by recent performance in TAC Slot Filling. We isolate this recall loss for NE slots by systematically analysing each stage of the slot filling pipeline as a filter over correct answers. Recall is critical as candidates never generated can never be recovered, whereas precision can always be increased in downstream processing. We provide precise, empirical confirmation of previously hypothesised sources of recall loss in slot filling. While NE type constraints substantially reduce the search space with only a minor recall penalty, we find that 10% to 39% of slot fills will be entirely ignored by most systems. One in six correct answers are lost if coreference is not used, but this can be mostly retained by simple name matching rules.

Cite

CITATION STYLE

APA

Pink, G., Nothman, J., & Curran, J. R. (2014). Analysing recall loss in named entity slot filling. In EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 820–830). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/d14-1089

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free