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This paper describes a method of semi-automatically acquiring an En-glish HPSG grammar from the Penn Treebank. First, heuristic rules are employed to annotate the treebank with partially-specified derivation trees. Lexical entries are automatically extracted from the annotated corpus by inversely applying schemata to partially-specified derivation trees. 1(More)
Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing methods learn statistics on trimming context-free grammar (CFG) rules. However, these methods sometimes eliminate the original meaning by incorrectly removing important parts of(More)
Many parsing techniques including parameter estimation assume the use of a packed parse forest for efficient and accurate parsing. However, they have several inherent problems deriving from the restriction of locality in the packed parse forest. Deterministic parsing is one of solutions that can achieve simple and fast parsing without the mechanisms of the(More)
This paper introduces a novel framework for the accurate retrieval of relational concepts from huge texts. Prior to retrieval, all sentences are annotated with predicate argument structures and ontological iden-tifiers by applying a deep parser and a term recognizer. During the run time, user requests are converted into queries of region algebra on these(More)
This paper describes an extremely lexi-calized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are defined with only the probabilities of selecting lexical entries. The proposed model is very simple, and experiments revealed that the implemented parser runs around four times faster than the previous(More)
Exogenous microglia pass through the blood-brain barrier and migrate to ischemic hippocampal lesions when injected into the circulation. We investigated the effect of exogenous microglia on ischemic CA1 pyramidal neurons. Microglia were isolated from neonatal mixed brain cultures, labeled with the fluorescent dye PKH26, and injected into the subclavian(More)
We investigated the performance efficacy of beam search parsing and deep parsing techniques in probabilistic HPSG parsing using the Penn treebank. We first tested the beam thresholding and iterative parsing developed for PCFG parsing with an HPSG. Next, we tested three techniques originally developed for deep parsing: quick check, large constituent(More)
We present a practical HPSG parser for English, an intelligent search engine to retrieve MEDLINE abstracts that represent biomedical events and an efficient MED-LINE search tool helping users to find information about biomedical entities such as genes, proteins, and the interactions between them.
This paper describes a log-linear model with an n-gram reference distribution for accurate probabilistic HPSG parsing. In the model, the n-gram reference distribution is simply defined as the product of the probabilities of selecting lexical entries, which are provided by the discriminative method with machine learning features of word and POS n-gram as(More)
This paper describes new default unification, lenient default unification. It works efficiently, and gives more informative results because it maximizes the amount of information in the result, while other default unification maximizes it in the default. We also describe robust processing within the framework of HPSG. We extract grammar rules from the(More)