Computer Science Named Entity Recognition in the Open Research Knowledge Graph

by   Jennifer D'Souza, et al.

Domain-specific named entity recognition (NER) on Computer Science (CS) scholarly articles is an information extraction task that is arguably more challenging for the various annotation aims that can beset the task and has been less studied than NER in the general domain. Given that significant progress has been made on NER, we believe that scholarly domain-specific NER will receive increasing attention in the years to come. Currently, progress on CS NER – the focus of this work – is hampered in part by its recency and the lack of a standardized annotation aim for scientific entities/terms. This work proposes a standardized task by defining a set of seven contribution-centric scholarly entities for CS NER viz., research problem, solution, resource, language, tool, method, and dataset. Following which, its main contributions are: combines existing CS NER resources that maintain their annotation focus on the set or subset of contribution-centric scholarly entities we consider; further, noting the need for big data to train neural NER models, this work additionally supplies thousands of contribution-centric entity annotations from article titles and abstracts, thus releasing a cumulative large novel resource for CS NER; and, finally, trains a sequence labeling CS NER model inspired after state-of-the-art neural architectures from the general domain NER task. Throughout the work, several practical considerations are made which can be useful to information technology designers of the digital libraries.


page 1

page 2

page 3

page 4


Domain-Transferable Method for Named Entity Recognition Task

Named Entity Recognition (NER) is a fundamental task in the fields of na...

Overview of STEM Science as Process, Method, Material, and Data Named Entities

We are faced with an unprecedented production in scholarly publications ...

ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts

Named entity recognition (NER) is an important task that aims to resolve...

WikiCSSH: Extracting and Evaluating Computer Science Subject Headings from Wikipedia

Hierarchical domain-specific classification schemas (or subject heading ...

Named Entity Recognition on Noisy Data using Images and Text (1-page abstract)

Named Entity Recognition (NER) is an important subtask of information ex...

Accelerated materials language processing enabled by GPT

Materials language processing (MLP) is one of the key facilitators of ma...

CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction

In order to construct or extend entity-centric and event-centric knowled...

Please sign up or login with your details

Forgot password? Click here to reset