Results of computational complexity exist for a wide range of phrase structure-based grammar formalisms, while there is an apparent lack of such results for dependency-based formalisms.

We augment a model of translation based on re-ordering nodes in syntactic trees in order to allow alignments not conforming to the original tree structure, while keeping computational complexity polynomial in the sentence length. This is done by adding a new subtree cloning operation to either tree-to-string or tree-to-tree alignment algorithms.

Morphological analysis must take into account the spelling-change processes of a language as well as its possi- ble configurations of stems, affixes, and infiectional markings. The computational difficulty of the task can be clari- fied by investigating specific models of morphological pro- cessing. The use of finite-state machinery in the "two- level"model by Kimmo Koskenniemi gives it the appear- ance of computational efficiency, but closer examination shows the model does not guarantee efficient processing. Reductions of the satisfiability problem show that finding the proper lexical/surface correspondence in a two-level generation or recognition problem can be computationally difficult. The difficulty increases if unrestricted deletions (null characters) are allowed.

Proponents of generalized phrase structure grammar (GPSG) cite its weak context-free generative power as proof of the computational tractability of GPSG-Recognition. Since context-free languages (CFLs) can be parsed in time proportional to the cube of the sentence length, and GPSGs only generate CFLs, it seems plausible that GPSGs can also be parsed in cubic time. This longstanding, widely-assumed GPSG "efficient parsability" result is misleading: parsing the sentences of an arbitrary GPSG is likely to be intractable, because a reduction from 3SAT proves that the universal recognition problem for the GPSGs of Gazdar (1981) is NP-hard. Crucially, the time to parse a sentence of a CFL can be the product of sentence length cubed and context-free grammar size squared, and the GPSG grammar can result in an exponentially large set of derived context-free rules. A central object in the 1981 GPSG theory, the metarule, inherently results in an intractable parsing problem, even when severely constrained. The implications for linguistics and natural language parsing are discussed.

An important goal of computational linguistics has been to use linguistic theory to guide the construction of computationally efficient real-world natural language processing systems. At first glance, generalized phrase structure grammar (GPSG) appears to be a blessing on two counts. First, the precise formalisms of GPSG might be a direct and fransparent guide for parser design and implementation. Second, since GPSG has weak context-free generative power and context-free languages can be parsed in O(n ~) by a wide range of algorithms, GPSG parsers would appear to run in polynomial time. This widely-assumed GPSG "efficient parsability " result is misleading: here we prove that the universal recognition problem for current GPSG theory is exponential-polynomial time hard, and assuredly intractable. The paper pinpoints sources of complexity (e.g. metarules and the theory of syntactic features) in the current GPSG theory and concludes with some linguistically and computationally motivated restrictions on GPSG. 1

In this paper, we analyze the different approaches taken to-date within the computer vision, robotics and artificial intelligence communities for the representation, recognition, synthesis and understanding of action. We deal with action at different levels of complexity and provide the reader with the necessary related literature references. We put the literature reference further into context and outline a possible interpretation of action by taking into account the different aspects of action recognition, action synthesis and task-level planning.

this paper. Because a GPSG is so closely related to a CFG, it was thought that the well-known efficient parsing techniques for CFGs could be applied, with modifications, to GPSGs, and that GPSGs would therefore be computationally tractable. Recently, however, Ristad (1985) has shown that this is not the case, and that the unrestricted GPSG parsing problem is NP-complete (on the total problem size, viz. grammar plus input sentence) . Even before Ristad's result was known, workers in this field had found the practical problems caused by the interaction of FCRs, FSDs, and the propagation conventions difficult to surmount. Briscoe's comments (1986) are typical: "Finally, the concept of privileged feature, its interaction with feature specification defaults and the bi-directionality of the head feature convention are all so complex that it is debatable how much use they would be in a practical system (even if we did manage to implement them)" (p. 1); "The interaction of feature co-occurrence restrictions, feature specification defaults and feature propagation proved very hard to implement/understand" (p. 2)

Abstract. The Earley algorithm is a widely used parsing method in natural language processing applications. We introduce a variant of Earley parsing that is based on a “delayed ” recognition of constituents. This allows us to start the recognition of a constituent only in cases in which all of its subconstituents have been found within the input string. This is particularly advantageous in several cases in which partial analysis of a constituent cannot be completed and in general in all cases of productions sharing some suffix of their right-hand sides (even for different left-hand side nonterminals). Although the two algorithms result in the same asymptotic time and space complexity, from a practical perspective our algorithm improves the time and space requirements of the original method, as shown by reported experimental results. 1

In this paper, I revise generalized phrase structure grammar (GPSG) linguistic theory so that it is more tractable and linguis- tically constrained. Revised GPSG is also easier to understand, use, and implement. I provide an account of topicalization, explicative pronouns, and parasitic gaps in the revised system and conclude with suggestions for efficient parser design.

We augment a model of translation based on re-ordering nodes in syntactic trees in order to allow alignments not conforming to the original tree structure, while keeping computational complexity polynomial in the sentence length. This is done by adding a new subtree cloning operation to either tree-to-string or tree-to-tree alignment algorithms.