Spectral Unsupervised Parsing with Additive Tree Metrics
Code (0)
등록된 구현이 없습니다.
Tasks
Language AcquisitionMatrix CompletionSimilar Papers 제목 키워드 기반
Identifiability and Unmixing of Latent Parse Trees
This paper explores unsupervised learning of parsing models along two directions. First, which models are identifiable from infinite data? We use a general technique for numerically checking identifiability based on th…
Dependency ParsingUnsupervised Full Constituency Parsing with Neighboring Distribution Divergence
Unsupervised constituency parsing has been explored much but is still far from being solved. Conventional unsupervised constituency parser is only able to capture the unlabeled structure of sentences. Towards unsupervise…
Constituency ParsingPOSSemantic SimilaritySemantic Textual SimilarityTree-Averaging Algorithms for Ensemble-Based Unsupervised Discontinuous Constituency Parsing
We address unsupervised discontinuous constituency parsing, where we observe a high variance in the performance of the only previous model in the literature. We propose to build an ensemble of different runs of the exist…
AllConstituency ParsingUnsupervised Dependency Parsing: Let's Use Supervised Parsers
We present a self-training approach to unsupervised dependency parsing that reuses existing supervised and unsupervised parsing algorithms. Our approach, called `iterated reranking' (IR), starts with dependency trees gen…
Dependency ParsingRerankingUnsupervised Dependency ParsingUnsupervised and Few-shot Parsing from Pretrained Language Models
Pretrained language models are generally acknowledged to be able to encode syntax [Tenney et al., 2019, Jawahar et al., 2019, Hewitt and Manning, 2019]. In this article, we propose UPOA, an Unsupervised constituent Parsi…
Language Modelling