DefExt: A Semi Supervised Definition Extraction Tool
원문 초록
We present DefExt, an easy to use semi supervised Definition Extraction Tool. DefExt is designed to extract from a target corpus those textual fragments where a term is explicitly mentioned together with its core features, i.e. its definition. It works on the back of a Conditional Random Fields based sequential labeling algorithm and a bootstrapping approach. Bootstrapping enables the model to gradually become more aware of the idiosyncrasies of the target corpus. In this paper we describe the main components of the toolkit as well as experimental results stemming from both automatic and manual evaluation. We release DefExt as open source along with the necessary files to run it in any Unix machine. We also provide access to training and test data for immediate use.
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Mathematical Entities: Corpora and Benchmarks
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Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition Extraction
DSC IIT-ISM at SemEval-2020 Task 6: Boosting BERT with Dependencies for Definition Extraction
UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition Extraction
A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency
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