Details
Date made available | 2021 |
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Publisher | Forschungsdaten-Repositorium der LUH |
Contact person | Sören Auer |
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Description
NLPContributionGraph was introduced as Task 11 at SemEval 2021 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. 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. The shared task has an open evaluation never-ending official online evaluation at Codalab.
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. The shared task has an open evaluation never-ending official online evaluation at Codalab.