We adapt the cognitively-oriented morphology acquisition model proposed in (Chan 2008) to perform morphological analysis, extending its concept of base-derived relationships to allow multi-step derivations and adding features required for robustness on noisy corpora. This results in a rule-based morphological analyzer which attains an F-score of 58.48% in… (More)
This paper introduces the probabilistic paradigm, a probabilistic, declarative model of morphological structure. We describe an algorithm that recursively applies Latent Dirichlet Allocation with an orthogonality constraint to discover morphological paradigms as the latent classes within a suffix-stem matrix. We apply the algorithm to data preprocessed in… (More)
—The Asymmetric Threat Response and Analysis Program (ATRAP) is a software system for intelligence fusion, visualization, reasoning, and prediction. ATRAP consists of a set of tools for annotating and automatically extracting entities and relationships from documents, visualizing this information in relational, geographic, and temporal dimensions, and… (More)
We use the Base and Transforms Model proposed by Chan  as the core of a morphological analyzer, extending its concept of base-derived relationships to allow multi-step derivations and adding a number of features required for robustness on larger corpora. The result is a rule-based morphological analyzer, attaining an F-score of 58.
The task we are investigating is unsupervised learning of natural language morphology for inflectional languages. The target morphological grammar consists of a lexicon of morphological base forms and transforms. A base form represents all inflections of a lexeme, and all base forms of the same POS category share the same fine-grained morphosyntactic type.… (More)