## NLPContributionGraph - Structuring Scholarly NLP Contributions in the Open Research Knowledge Graph ### Background [__NLPContributionGraph__](https://ncg-task.github.io/) was introduced as Task 11 at [SemEval 2021](https://semeval.github.io/SemEval2021/tasks) for the first time. The task is defined on a dataset of Natural Language Processing (NLP) scholarly articles with their contributions structured to be integrable within Knowledge Graph infrastructures such as the [Open Research Knowledge Graph](https://www.orkg.org/). The structured contribution annotations are provided as (1) __Contribution sentences__ : a set of sentences about the contribution in the article; (2) __Scientific terms and relations__: a set of scientific terms and relational cue phrases extracted from the contribution sentences; and (3) __Triples__: semantic statements that pair scientific terms with a relation, modeled toward subject-predicate-object RDF statements for KG building. The Triples are organized under three (mandatory) or more of twelve total information units (viz., _ResearchProblem_, _Approach_, _Model_, _Code_, _Dataset_, _ExperimentalSetup_, _Hyperparameters_, _Baselines_, _Results_, _Tasks_, _Experiments_, and _AblationAnalysis_). ### The Shared Task As a complete submission for the Shared Task, given NLP scholarly articles in plaintext format, systems had to automatically extract the following information: * contribution sentences; * scientific term and predicate phrases from the sentences; and * (subject,predicate,object) triple statements toward KG building organized under three or more of twelve total information units.