An Effective Transition-based Model for Discontinuous NER
Unlike widely used Named Entity Recognition (NER) data sets in generic domains, biomedical NER data sets often contain mentions consisting of discontinuous spans. Conventional sequence tagging techniques encode Markov assumptions that are efficient but preclude recovery of these mentions. We propose a simple, effective transition-based model with generic neural encoding for discontinuous NER. Through extensive experiments on three biomedical data sets, we show that our model can effectively recognize discontinuous mentions without sacrificing the accuracy on continuous mentions.
Code (1)
Tasks
modelnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NERSimilar Papers 제목 키워드 기반
Incremental Discontinuous Phrase Structure Parsing with the GAP Transition
This article introduces a novel transition system for discontinuous lexicalized constituent parsing called SR-GAP. It is an extension of the shift-reduce algorithm with an additional gap transition. Evaluation on two Ger…
Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle
We introduce a novel transition system for discontinuous constituency parsing. Instead of storing subtrees in a stack --i.e. a data structure with linear-time sequential access-- the proposed system uses a set of parsing…
Constituency ParsingSentenceUnlexicalized Transition-based Discontinuous Constituency Parsing
Lexicalized parsing models are based on the assumptions that (i) constituents are organized around a lexical head (ii) bilexical statistics are crucial to solve ambiguities. In this paper, we introduce an unlexicalized t…
Constituency ParsingSwitching state space model for simultaneously estimating state transitions and nonstationary firing rates
We propose an algorithm for simultaneously estimating state transitions among neural states, the number of neural states, and nonstationary firing rates using a switching state space model (SSSM). This model enables us …
Rethinking Boundaries: End-To-End Recognition of Discontinuous Mentions with Pointer Networks
A majority of research interests in irregular (eg, nested or discontinuous) named entity recognition (NER) have been paid on nested entities, while discontinuous entities received limited attention. Existing work for dis…
Boundary DetectionDecodernamed-entity-recognitionNamed Entity Recognition+2