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Extending prior work in Graf (2018, 2020, 2022c), I show that movement is tier-based strictly local (TSL) even if one analyzes it as a transformation, i.e. a tree transduction from derivation trees to output trees. I define input strictly local (ISL) tree-to-tree transductions with (lexical) TSL tests as a tier-based extension of ISL tree-to-tree transductions. TSL tests allow us to attach each mover to all its landing sites. In general, this class of transductions fails to attach each mover to its final landing site to the exclusion of all its intermediate landing sites, which is crucial for producing output trees with the correct string yield. The problem is avoided, though, if syntax enforces a variant of the Ban on Improper Movement. Subregular complexity thus provides a novel motivation for core restrictions on movement while also shedding new light on the choice between copies and traces in syntax.
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Curbing Feature Coding: Strictly Local Feature Assignment
Graf (2017) warns that every syntactic formalism faces a severe overgeneration problem because of the hidden power of subcategorization. Any constraint definable in monadic second-order logic can be compiled into the category system so that it is indirectly enforced as part of subcategorization. Not only does this kind of feature coding deprive syntactic proposals of their empirical bite, it also undermines computational efforts to limit syntactic formalisms via subregular complexity. This paper presents a subregular solution to feature coding. Instead of features being a cheap resource that comes for free, features must be assigned by a transduction. In particular, category features must be assigned by an input strictly local (ISL) tree-tot-tree transduction, defined here for the first time. The restriction to ISL transductions correctly rules out various deviant category systems.
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- Award ID(s):
- 1845344
- PAR ID:
- 10140839
- Date Published:
- Journal Name:
- Proceedings of the Society for Computation in Linguistics
- Volume:
- 3
- Page Range / eLocation ID:
- 362-371
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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