Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Statistical Decision-Tree Models for Parsing   Syntactic natural language parsers have shown themselves to be inadequate for
processing highly-ambiguous large-vocabulary text, as is evidenced by their
poor performance on domains like the Wall Street Journal, and by the movement
away from parsing-based approaches to text-processing in general. In this
paper, I describe SPATTER, a statistical parser based on decision-tree learning
techniques which constructs a complete parse for every sentence and achieves
accuracy rates far better than any published result. This work is based on the
following premises: (1) grammars are too complex and detailed to develop
manually for most interesting domains; (2) parsing models must rely heavily on
lexical and contextual information to analyze sentences accurately; and (3)
existing {$n$}-gram modeling techniques are inadequate for parsing models. In
experiments comparing SPATTER with IBM's computer manuals parser, SPATTER
significantly outperforms the grammar-based parser. Evaluating SPATTER against
the Penn Treebank Wall Street Journal corpus using the PARSEVAL measures,
SPATTER achieves 86\% precision, 86\% recall, and 1.3 crossing brackets per
sentence for sentences of 40 words or less, and 91\% precision, 90\% recall,
and 0.5 crossing brackets for sentences between 10 and 20 words in length.

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The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
3
The categories of this paper are: physics
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The categories of this paper are: bayes-an
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The categories of this paper are: quant-ph
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The categories of this paper are: q-fin
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The categories of this paper are: math-ph