Parse Tree Fragmentation of Ungrammatical Sentences

Abstract

Ungrammatical sentences present challenges for statistical parsers because the well-formed trees they produce may not be appropriate for these sentences. We introduce a framework for reviewing the parses of ungrammatical sentences and extracting the coherent parts whose syntactic analyses make sense. We call this task parse tree fragmentation. In this paper, we propose a training methodology for fragmenting parse trees without using a task-specific annotated corpus. We also propose some fragmentation strategies and compare their performance on an extrinsic task - fluency judgments in two domains: English-as-a-Second Language (ESL) and machine translation (MT). Experimental results show that the proposed fragmentation strategies are competitive with existing methods for making fluency judgments; they also suggest that the overall framework is a promising way to handle syntactically unusual sentences. PDF

Cite

Text

Hashemi and Hwa. "Parse Tree Fragmentation of Ungrammatical Sentences." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Hashemi and Hwa. "Parse Tree Fragmentation of Ungrammatical Sentences." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/hashemi2016ijcai-parse/)

BibTeX

@inproceedings{hashemi2016ijcai-parse,
  title     = {{Parse Tree Fragmentation of Ungrammatical Sentences}},
  author    = {Hashemi, Homa B. and Hwa, Rebecca},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {2796-2802},
  url       = {https://mlanthology.org/ijcai/2016/hashemi2016ijcai-parse/}
}