Natural language inference for arabic using extended tree edit distance with subtrees

Research output: Contribution to journalArticle

  • Authors:
  • Maytham Alabbas
  • Allan Ramsay


Many natural language processing (NLP) applications require the computation of similarities between pairs of syntactic or semantic trees. Many researchers have used tree edit distance for this task, but this technique suffers from the drawback that it deals with single node operations only. We have extended the standard tree edit distance algorithm to deal with subtree transformation operations as well as single nodes. The extended algorithm with subtree operations, TED+ST, is more effective and flexible than the standard algorithm, especially for applications that pay attention to relations among nodes (e.g. in linguistic trees, deleting a modifier subtree should be cheaper than the sum of deleting its components individually). We describe the use of TED+ST for checking entailment between two Arabic text snippets. The preliminary results of using TED+ST were encouraging when compared with two string-based approaches and with the standard algorithm. © 2013 AI Access Foundation.

Bibliographical metadata

Original languageEnglish
Pages (from-to)1-22
Number of pages21
JournalJournal of Artificial Intelligence Research
Publication statusPublished - Oct 2013