1 research outputs found
Finding People's Professions and Nationalities Using Distant Supervision - The FMI@SU "goosefoot" team at the WSDM Cup 2017 Triple Scoring Task
We describe the system that our FMI@SU student's team built for participating
in the Triple Scoring task at the WSDM Cup 2017. Given a triple from a
"type-like" relation, profession or nationality, the goal is to produce a
score, on a scale from 0 to 7, that measures the relevance of the statement
expressed by the triple: e.g., how well does the profession of an Actor fit for
Quentin Tarantino? We propose a distant supervision approach using information
crawled from Wikipedia, DeletionPedia, and DBpedia, together with task-specific
word embeddings, TF-IDF weights, and role occurrence order, which we combine in
a linear regression model. The official evaluation ranked our submission 1st on
Kendall's Tau, 7th on Average score difference, and 9th on Accuracy, out of 21
participating teams.Comment: Triple Scorer at WSDM Cup 2017, see arXiv:1712.0808