---
title: "Efficient HPSG Parsing with Supertagging and CFG-Filtering"
authors:
  - "Takuya Matsuzaki"
  - "Yusuke Miyao"
  - "Jun&apos;ichi Tsujii"
doi: ""
url: "https://ijcai.org/proceedings/2007/270"
pdf: "https://ijcai.org/proceedings/2007/0270.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "1671-1675"
track: ""
keywords:
---

# Efficient HPSG Parsing with Supertagging and CFG-Filtering

Takuya Matsuzaki, Yusuke Miyao, Jun&apos;ichi Tsujii

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 1671-1675.

## Abstract

An efficient parsing technique for HPSG is presented. Recent research has shown that supertagging is a key technology to improve both the speed and accuracy of lexicalized grammar parsing. We show that further speed-up is possible by eliminating non-parsable lexical entry sequences from the output of the supertagger. The parsability of the lexical entry sequences is tested by a technique called CFG-filtering, where a CFG that approximates the HPSG is used to test it. Those lexical entry sequences that passed through the CFG-filter are combined into parse trees by using a simple shift-reduce parsing algorithm, in which structural ambiguities are resolved using a classifier and all the syntactic constraints represented in the original grammar are checked. Experimental results show that our system gives comparable accuracy with a speed-up by a factor of six (30 msec/sentence) compared with the best published result using the same grammar.
