Figure 1: Our START system answering a complex question with the answer including contextual information regarding how the question was answered.
START's ternary expressions (subject–relation–object triples) can richly and efficiently represent the user's questions, as well as natural language annotations used to describe content, and therefore lend themselves well to syntactic decomposition of complex questions (see   and related abstracts). For further information on syntactic decomposition, see .
We may approach syntactic decomposition from two directions: first, syntax, and second, meta-knowledge about the contents of available information resources. Syntax informs us of which decompositions of a question are legal, and meta-knowledge about information resources can guide the system to answerable subquestions when many legal decompositions exist.
Legal syntactic decompositions are proper branches of the parse tree. Figure 2 shows two proper and one improper branch. The structure of a sentence, of course, is related to the meaning conveyed by the sentence. For example, if asked "Who was the third Republican president?", we must first find the Republican presidents (Lincoln, Grant, Hayes, Garfield, ...) and then find the third one, rather than first finding the third president (John Adams), and then seeing if he was a Republican. The relation which is lower in the parse tree must be resolved first, with two exceptions:
Figure 2: Proper branches are outlined in green, improper in yellow. For efficient knowledge matching, the larger branch (labeled #1) should be tried first and the smaller (#2) second.
We plan to examine more closely the relation between syntax and legal decompositions, with particular attention to the validity of resolving a relation before another relation which is lower in the parse tree: Is it strictly the case that doing so makes it impossible to guarantee a correct interpretation of the sentence, or may higher relations be resolved first provided they are within the same projection, island, clause, or other syntactic element?
We also plan to further explore the relation between the "shape" of the knowledge base (as indicated by available annotations) and the path of resolving a complex query, in order to further increase the efficiency of our search.
This work is supported in part by the Disruptive Technology Office as part of the AQUAINT Phase 3 research program.
 Boris Katz. Using English for Indexing and Retrieving. In Artificial Intelligence at MIT: Expanding Frontiers, v. 1; Cambridge, MA, 1990.
 Boris Katz. Annotating the World Wide Web Using Natural Language. In Proceedings of the 5th RIAO Conference on Computer Assisted Information Searching on the Internet (RIAO '97), Montreal, Canada, 1997.
 Boris Katz, Gary Borchardt, and Sue Felshin. Syntactic and Semantic Decomposition Strategies for Question Answering from Multiple Resources. In Proceedings of the AAAI 2005 Workshop on Inference for Textual Question Answering, pp. 35–41, 2005.
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