2,030 research outputs found
Using Decision Trees for Coreference Resolution
This paper describes RESOLVE, a system that uses decision trees to learn how
to classify coreferent phrases in the domain of business joint ventures. An
experiment is presented in which the performance of RESOLVE is compared to the
performance of a manually engineered set of rules for the same task. The
results show that decision trees achieve higher performance than the rules in
two of three evaluation metrics developed for the coreference task. In addition
to achieving better performance than the rules, RESOLVE provides a framework
that facilitates the exploration of the types of knowledge that are useful for
solving the coreference problem.Comment: 6 pages; LaTeX source; 1 uuencoded compressed EPS file (separate);
uses ijcai95.sty, named.bst, epsf.tex; to appear in Proc. IJCAI '9
Automating Coreference: The Role of Annotated Training Data
We report here on a study of interannotator agreement in the coreference task
as defined by the Message Understanding Conference (MUC-6 and MUC-7). Based on
feedback from annotators, we clarified and simplified the annotation
specification. We then performed an analysis of disagreement among several
annotators, concluding that only 16% of the disagreements represented genuine
disagreement about coreference; the remainder of the cases were mostly
typographical errors or omissions, easily reconciled. Initially, we measured
interannotator agreement in the low 80s for precision and recall. To try to
improve upon this, we ran several experiments. In our final experiment, we
separated the tagging of candidate noun phrases from the linking of actual
coreferring expressions. This method shows promise - interannotator agreement
climbed to the low 90s - but it needs more extensive validation. These results
position the research community to broaden the coreference task to multiple
languages, and possibly to different kinds of coreference.Comment: 4 pages, 5 figures. To appear in the AAAI Spring Symposium on
Applying Machine Learning to Discourse Processing. The Alembic Workbench
annotation tool described in this paper is available at
http://www.mitre.org/resources/centers/advanced_info/g04h/workbench.htm
Comparing knowledge sources for nominal anaphora resolution
We compare two ways of obtaining lexical knowledge for antecedent selection in other-anaphora
and definite noun phrase coreference. Specifically, we compare an algorithm that relies on links
encoded in the manually created lexical hierarchy WordNet and an algorithm that mines corpora
by means of shallow lexico-semantic patterns. As corpora we use the British National
Corpus (BNC), as well as the Web, which has not been previously used for this task. Our
results show that (a) the knowledge encoded in WordNet is often insufficient, especially for
anaphor-antecedent relations that exploit subjective or context-dependent knowledge; (b) for
other-anaphora, the Web-based method outperforms the WordNet-based method; (c) for definite
NP coreference, the Web-based method yields results comparable to those obtained using
WordNet over the whole dataset and outperforms the WordNet-based method on subsets of the
dataset; (d) in both case studies, the BNC-based method is worse than the other methods because
of data sparseness. Thus, in our studies, the Web-based method alleviated the lexical knowledge
gap often encountered in anaphora resolution, and handled examples with context-dependent relations
between anaphor and antecedent. Because it is inexpensive and needs no hand-modelling
of lexical knowledge, it is a promising knowledge source to integrate in anaphora resolution systems
Recommended from our members
Lexical patterns, features and knowledge resources for coreference resolution in clinical notes
Generation of entity coreference chains provides a means to extract linked narrative events from clinical notes, but despite being a well-researched topic in natural language processing, general- purpose coreference tools perform poorly on clinical texts. This paper presents a knowledge-centric and pattern-based approach to resolving coreference across a wide variety of clinical records comprising discharge summaries, progress notes, pathology, radiology and surgical reports from two corpora (Ontology Development and Information Extraction (ODIE) and i2b2/VA). In addition, a method for generating coreference chains using progressively pruned linked lists is demonstrated that reduces the search space and facilitates evaluation by a number of metrics. Independent evaluation results show an F-measure for each corpus of 79.2% and 87.5%, respectively, which offers performance at least as good as human annotators, greatly increased performance over general- purpose tools, and improvement on previously reported clinical coreference systems. The system uses a number of open-source components that are available to download
- …