2000 ANovelUseStatParsingToIE

• (Miller et al., 2000) ⇒ Scott Miller, Heidi Fox, Lance Ramshaw, and Ralph Weischedel. (2000). “A Novel Use of Statistical Parsing to Extract Information from Text.” In: Proceedings of the 1st North American Chapter of the Association for Computational Linguistics Conference (NAACL 2000).

Subject Headings: Relation Recognition from Text Algorithm, (Miller et al., 1998), Joint Inference Algorithm.

Notes

• It is a Seminal Paper on a Joint Inference Algorithm.
• It adds a simple entity mention and relation mention annotation on top of syntactic annotation, and trains a parser to predict both annotations in parallel on a new Document.
• It finished in second place on MUC-7.

Cited By

• ~141 http://scholar.google.com/scholar?cites=13704129471963223087
• http://www.cis.upenn.edu/~edloper/notes/papers/Miller,_Fox,_Ramshaw,_Weishcedel_2000.html
  • "The parser model uses interpolated MLE estimates, with separate models for modifier consituents, POS tags, head words, and word features. The model is searched using a CKY-style chart parser, with pruning of low-probability elements.

2006

• (Zhang et al., 2006b) ⇒ Min Zhang, Jie Zhang, and Jian Su. (2006). “Exploring Syntactic Features for Relation Extraction using a Convolution Tree Kernel.” In: Proceedings of HLT Conference (HLT 2006).
  • QUOTE: Miller et al. (2000) address the task of Relation Extraction from the statistical parsing viewpoint. They integrate various tasks such as POS tagging, NE tagging, template extraction and relation extraction into a Generative Model. Their results essentially depend on the entire full parse tree."

2005

• (Zhao & Grishman, 2005) ⇒ Shubin Zhao, and Ralph Grishman. (2005). “Extracting Relations with Integrated Information Using Kernel Methods.” In: Proceedings of ACL Conference (ACL 2005).
  • QUOTE: Collins et al. (1997) and Miller et al. (2000) used statistical parsing models to extract relational facts from text, which avoided pipeline processing of data. However, their results are essentially based on the output of sentence parsing, which is a deep processing of text. So their approaches are vulnerable to errors in parsing. Collins et al. (1997) addressed a simplified task within a confined context in a target sentence.

Quotes

Abstract

Since 1995, a few statistical parsing algorithms have demonstrated a breakthrough in parsing accuracy, as measured against the UPenn TREEBANK as a gold standard. In this paper we report adapting a lexicalized, probabilistic context-free parser to information extraction and evaluate this new technique on MUC-7 template elements and template relations."

References

• Bikel, Dan; S. Miller; R. Schwartz; and R. Weischedel. (1997) “NYMBLE: A High-Performance Learning Name-finder.” In: Proceedings of the Fifth Conference on Applied Natural Language Processing, Association for Computational Linguistics, pp. 194-201.
• Collins, Michael. (1996) “A New Statistical Parser Based on Bigram Lexical Dependencies.” In: Proceedings of the 34th Annual Meeting of the Association for Computational Linguistics, pp. 184-191.
• Collins, Michael. (1997) “Three Generative, Lexicalised Models for Statistical Parsing.” In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, pp. 16-23.
• Marcus, M.; B. Santorini; and M. Marcinkiewicz. (1993) “Building a Large Annotated Corpus of English: the Penn Treebank.” Computational Linguistics, 19(2):313-330.
• Goodman, Joshua. (1997) “Global Thresholding and Multiple-Pass Parsing.” In: Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, pp. 11-25.
• Placeway, P., R. Schwartz, et al. (1993). “The Estimation of Powerful Language Models from Small and Large Corpora.” IEEE ICASSP
• Weischedel, Ralph; Marie Meteer; Richard Schwartz; Lance Ramshaw; and Jeff Palmucci. (1993) “Coping with Ambiguity and Unknown Words through Probabilistic Models.” Computational Linguistics, 19(2):359-382.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2000 ANovelUseStatParsingToIE	Scott Miller Heidi Fox Ralph Weischedel Lance A. Ramshaw			A Novel Use of Statistical Parsing to Extract Information from Text			http://acl.ldc.upenn.edu/A/A00/A00-2030.pdf