Enhancing Unsupervised Generative Dependency Parser with Contextual Information (P19-1)
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| Challenge: | Existing approaches to unsupervised dependency parsing are based on probabilistic generative models that learn the joint distribution of the given sentence and its parse. |
| Approach: | They propose a probabilistic model that generates a sentence and its parse from a latent representation, which encodes global contextual information of the generated sentence. |
| Outcome: | The proposed model achieves competitive accuracy compared with state-of-the-art models. |
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