We study the opportunity for using crowdsourcing methods to acquire language corpora for use in natural language processing systems. Specifically, we empirically investigate three methods for eliciting natural language sentences that correspond to a given semantic form. The methods convey frame semantics to crowd workers by means of sentences, scenarios, and list-based descriptions. We discuss various performance measures of the crowdsourcing process, and analyze the semantic correctness, naturalness, and biases of the collected language. We highlight research challenges and directions in applying these methods to acquire corpora for natural language processing applications.<\/p>\n","protected":false},"excerpt":{"rendered":"
We study the opportunity for using crowdsourcing methods to acquire language corpora for use in natural language processing systems. Specifically, we empirically investigate three methods for eliciting natural language sentences that correspond to a given semantic form. The methods convey frame semantics to crowd workers by means of sentences, scenarios, and list-based descriptions. We discuss 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