Name
Abstract | ||
|---|---|---|
The Penn Treebank encodes valuable information such as grammatical function, semantic roles, and identification of traces. The addition of such information was intended to facilitate the process of predicate-argument extraction. However, even with the enriched annotation this task is far from trivial and, to our knowledge, no complete set of predicate argument structures derived from the Treebank exists. Our paper describes a method for retrieving predicate-argument structures that circumvents the complexity of the tree structures in the corpus, while employing few template rules. Our system operates on a flattened, morphologically enriched version of the corpus. This flattened representation allows access to all levels of the tree simultaneously and thus enables the detection of the main sentence constituents by means of simple template rules. A small number of rules apply to identify the head words of each constituent and the latter fill in the constituent templates, to build the logical forms representative of the predicate argument structure. The system is robust in the face of incomplete syntactic coverage. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.3115/1072228.1072333 | COLING |
Keywords | Field | DocType |
template rule,predicate-argument structure,penn treebank,simple template rule,constituent template,enriched annotation,predicate argument structure,predicate-argument extraction,morphologically enriched version,main sentence constituent,tree structure,logical form | Annotation,Computer science,Tree structure,Artificial intelligence,Natural language processing,Treebank,Predicate (grammar),Template,Sentence,Syntax,Semantic role labeling | Conference |
Volume | Citations | PageRank |
C02-1 | 8 | 1.10 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Liakata | 1 | 375 | 30.40 |
| Stephen Pulman | 2 | 450 | 38.31 |