Phase-based Minimalist Parsing and complexity in non-local dependencies
Authors: Cristiano Chesi (IUSS, 2017)
Topic: Syntax and Dependency Treebanks

Abstract
A cognitively plausible parsing algorithm should perform like the human parser in critical contexts. Here I propose an adaptation of Earley’s parsing algorithm, suitable for Phase-based Minimalist Grammars AUTHOR, that is able to predict complexity effects in performance. Focusing on self-paced reading experiments of object clefts sentences AUTHOR I will associate to parsing a complexity metric based on cued features to be retrieved at the verb segment (Feature Retrieval & Encoding Cost, FREC). FREC is crucially based on the usage of memory predicted by the discussed parsing algorithm and it correctly fits with the reading time revealed.

Introduction
The last twenty years of formal linguistic research have been deeply influenced by Chomsky’s minimalist intuitions (Chomsky 1995, 2013). In a nutshell, the core Minimalist proposal is to reduce phrase structure formation to the recursive application of a binary, bottom-up, structure-building operation dubbed Merge. Merge creates hierarchical structures by combining two lexical items (1.a), one lexical item and an already built (by previous application of Merge operations) phrase (1.b) or two already built phrases (1.c). Phrases are not linearly ordered by Merge. Only when they are spelled-out (i.e. sent to the SensoryMotor interface, aka Phonetic Form, PF), linearization is required: assuming that x and y are terminal nodes (i.e. words), either <x, y> or <y, x> can both be proper linearizations of (1.a). Hierarchical structure (and linearization) is also determined by another structure building operation: Move (or Internal Merge, Chomsky 1995); Move re-arranges phrases in the structure by re-merging an item (already merged in the structure) to the edge of the current, top-most, phrase: for instance [XP [YP [ZP]]] can lead to [ZP [XP [YP (ZP)]] if XP (the probe) has a feature triggering movement (e.g. +f) and ZP (the goal) has the relevant feature qualifying it as a plausible target for movement (e.g. -f). At the end, the element displaced (ZP) will occupy the edge of the structure. When the items within an already built phrase, for instance XP, are delivered to PF, they get properly linearized according to their hierarchical structure (e.g. Linear Correspondence Axiom, Kayne 1994), intrinsic phonetic properties (e.g. cliticization), as well as economy conditions (e.g. an items should not be pronounced twice). Such a (cyclic) spellout happens at phases: XP will be delivered to PF only if it qualifies as a phase (Chomsky 2013). In this sense, a phase should be a constituent/phrase with some degree of completeness with respect to semantic interpretation (Logic Form, aka LF). Most minimalist linguists agree on the fact that a full-fledged sentence (aka Complementizer Phrase, CP) is a phase, the highest argumental shell of a predicate qualifies as a phase (aka littlev Phrase, vP) and also a full argument is a phase (aka Determiner Phrase, DP). Such a simple (and computationally appealing) model has been fully formalized (Stabler 1997, Collins & Stabler 2016) and some parsing algorithm that implements main minimalist insights has been discussed in literature (e.g. Harkema 2001, Chesi 2012 a.o.). In these pages, I will present some of the advantages of retaining such a simplified computational approach to syntactic derivation. Crucially, I will try to overcome some clear disadvantages in assuming the just presented standard, bottom-up, structure building operations, while obtaining, at the same time, a better empirical fit: on the one hand, I will avoid any non-efficient deductiveparsing perspective (that is a consequence of the assumed bottom-up nature of the Merge and Move operations); on the other, I will promote a more transparent relation between formal competence, parsing and psycholinguistic performance by presenting a simple adaptation of Earley’s Top-Down parsing algorithm (Earley 1970) and a complexity metric that refers directly to parsing memory usage: this metric will be able to account for complexity in retrieving the correct item while processing specific non-local dependencies. By “non-local” dependencies I refer to those relations involving movement, namely constructions where the very same item occurs in two distinct, non-adjacent, positions: for instance, wh-dependencies in English require the whitem (who, in (1)) to be interpreted both in a the left peripheral (focalized) position (the Criterial position, in the sense of Rizzi 2007) and in the thematic lower position (right next to the verb meet in (1))1: (1) Who1 do you think Mary will meet _1? The critical derivation I will discuss in this paper is that of object clefts (Gordon et al. 2001) that with wh-questions share a similar non-local dependency formation: (2) a. It is [DP1 the banker|John|me] that [DP2 the lawyer|Dan|you] will meet _DP1 In short, the head of the dependency (DP1) should be interpreted both as a focalized item and as the direct object (this is where the name of the construction “object cleft” comes from) of the embedded verb. The difficulty of parsing this structure has been deeply discussed in literature (Gordon et al. 2004). What is considered a crucial factor is the role of the similarity between DP1 and DP2 (the subject of the cleft, Belletti and Rizzi 2013, §2). To capture this fact, I will re-adapt Earley’s algorithm (§3.1) to operate on a specific version of Minimalist Grammar (§3). This would allow us to subsume the similarity effect by predicting reading differences as revealed in self-paced reading experiments (e.g. Warren & Gibson 2005, §4).

Conclusion
In this paper I presented an adaptation of Earley’s Top-Down parsing algorithm to be used with a simple implementation of a Minimalist Grammar (PMG). The advantages of this approach are both in terms of cognitive plausibility and parsing/performance transparency. From the cognitive plausibility perspective, I showed how a re-orientation of the minimalist structure building operations Merge and Move is sufficient to include such operations directly within a parsing procedure. This is a step toward the “Parser Is the Grammar” (PIG) default hypothesis (Phillips 2006) and a welcome simplification of the linguistic competence description: such a grammar description (i.e. our linguistic competence) is shared both in production (generation) and in comprehension (parsing); this seems trivial from a cognitive perspective (we have a unique Broca’s area activated in syntactic processing both in parsing and in generation), but it is far from trivial in computational terms. On the other hand, from the parsing/performance transparency perspective, I presented a complexity metric (FREC), based on cued features stored in memory which better characterize performance in object clefts constructions compared to alternative models: for instance the Depencency Locality Theory (DLT) based on accessibility hierarchy (Gibson 2000) is unable to predict high complexity in N-N condition comparable to N-D or D-D condition, since N should be uniformly more accessible than D, contrary to the facts. The proposed model, obviously should be extended in many respects to capture other critical phenomena (see Lewis & Vasishth 2005) but the first results on specific well-studied constructions, like object clefts, seem very promising.