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The rational index ρ L of a language L is an integer function, where ρ L (n) is the maximum length of the shortest string in L ∩ R , over all regular languages R recognized by n-state nondeterministic finite automata (NFA). This paper investigates the rational index of languages defined by grammars with bounded parse tree dimension: this is a numerical measure of the amount of branching in a tree (with trees in a linear grammar having dimension 1). For context-free grammars, a grammar with tree dimension bounded by d has rational index at most O (n 2 d) , and it is known from the literature that there exists a grammar with rational index Θ (n 2 d) . In this paper, it is shown that for multi-component grammars with at most k components (k-MCFG) and with a tree dimension bounded by d, the rational index is at most O (n 2 k d) , where the constant depends on the grammar, and there exists such a grammar with rational index k 2 k d 2 - k d - 2 k - 1 · (8 k + 1) 2 k d n 2 k d . Also, for the case of ordinary context-free grammars, a more precise lower bound 1 2 d 2 + d - 3 3 2 d n 2 d is established. [ABSTRACT FROM AUTHOR]

Introduction: Broca and Wernicke's patients perform satisfactorily regarding the processing of canonical syntactic structures, as maintained by previous studies; however, there has been a gap in the literature because no particular research has yet investigated the performance of these patients in the Persian circumstances once they were required to analyze sentences which would demand extra-semantic processing. This study clarifies the role of two critical semantic operations demanding extra-semantic processing at the sentential level: Aspectual coercion. It complements to provide some evidence on the localist view of the brain. Our rationale for selecting these operations was their pure semantic nature, not relying on morphosyntactic properties. Materials and Methods: Having recruited two age- and education-matched Broca, two Wernicke, and four healthy controls, we conducted a semantic judgment task in which the participants were asked to express their correct semantic judgment in the two coercion and two normal conditions. Results: Our results showed an approximately above-chance performance of the Broca group for all conditions; however, in the Wernicke group, the same result was not observed due to their poor performance in coercion conditions, though in ordinary sentences, they performed much better. Conclusion: Our findings, along with similar off-line and imaging studies, corroborate the view of localism, based on which Wernicke's area is mainly responsible for the primary semantic operations while Broca's area predominantly takes over syntactic parsing. [ABSTRACT FROM AUTHOR]

In this article, we present a derivative-based, functional recognizer and parser generator for visibly pushdown grammars. The generated parser accepts ambiguous grammars and produces a parse forest containing all valid parse trees for an input string in linear time. Each parse tree in the forest can then be extracted also in linear time. Besides the parser generator, to allow more flexible forms of the visibly pushdown grammars, we also present a translator that converts a tagged CFG to a visibly pushdown grammar in a sound way, and the parse trees of the tagged CFG are further produced by running the semantic actions embedded in the parse trees of the translated visibly pushdown grammar. The performance of the parser is compared with popular parsing tools, including ANTLR, GNU Bison, and other popular hand-crafted parsers. The correctness and the time complexity of the core parsing algorithm are formally verified in the proof assistant Coq. [ABSTRACT FROM AUTHOR]

A large amount of sentence-processing work has focused on revealing how the parser incrementally integrates each incoming word into the current linguistic representation. It is often explicitly or implicitly assumed that the structure endorsed by the parser should determine the ultimate interpretation of the sentence. The current study investigates whether the interpretive bias in sentence comprehension necessarily tracks the parsing bias. Our case study concerns the locality bias in nonlocal dependencies, specifically Mandarin wh-in-situ scope dependencies. Our findings suggest a misalignment between parsing and interpretative decisions at the global level. In particular, for Mandarin wh-in-situ constructions that involve scope ambiguity, there is a locality bias in parsing, but an antilocality bias in interpretation. Building upon the rational speech act framework, we propose a Bayesian pragmatic analysis to account for these findings. Under our proposal, the seeming conflict between parsing and interpretation will ultimately disappear because parsing preferences will be naturally embedded under the pragmatic reasoning process to generate the ultimate interpretation. The current study therefore makes novel contributions, both empirically and theoretically, to addressing the broader question about the relationship between parsing and interpretation.* [ABSTRACT FROM AUTHOR]

Formal constraints on crossing dependencies have played a large role in research on the formal complexity of natural language grammars and parsing. Here we ask whether the apparent evidence for constraints on crossing dependencies in treebanks might arise because of independent constraints on trees, such as low arity and dependency length minimization. We address this question using two sets of experiments. In Experiment 1, we compare the distribution of formal properties of crossing dependencies, such as gap degree, between real trees and baseline trees matched for rate of crossing dependencies and various other properties. In Experiment 2, we model whether two dependencies cross, given certain psycholinguistic properties of the dependencies. We find surprisingly weak evidence for constraints originating from the mild context-sensitivity literature (gap degree and well-nestedness) beyond what can be explained by constraints on rate of crossing dependencies, topological properties of the trees, and dependency length. However, measures that have emerged from the parsing literature (e.g., edge degree, end-point crossings, and heads' depth difference) differ strongly between real and random trees. Modeling results show that cognitive metrics relating to information locality and working-memory limitations affect whether two dependencies cross or not, but they do not fully explain the distribution of crossing dependencies in natural languages. Together these results suggest that crossing constraints are better characterized by processing pressures than by mildly context-sensitive constraints. [ABSTRACT FROM AUTHOR]

This article proposes a political economy approach to the grammar of institutions, by building on the study of contracts in economics. First, I argue that more attention needs to be paid to the costs and benefits of institutions, thus allowing researchers to derive empirically testable hypotheses on the evolution of institutions. In this vein, the role of conditions in studying the grammar of institutions becomes central. Second, I propose, validate, and test an innovative method to study the grammar, based on computational linguistics. This method allows extracting the elements of the grammar in an automated and unsupervised manner, paving the way to large‐N analyses. In so doing, this article seeks to bridge the gap between public policy and political economy. [ABSTRACT FROM AUTHOR]

How did grammar evolve? Perhaps a better way to ask the question is what kind of cognition is needed to enable grammar. The present analysis departs from the observation that linguistic communication is structured in terms of agents and patients, a reflection of how humans see the world. One way to explore the origins of cognitive skills in humans is to compare them with primates. A first approach has been to teach great apes linguistic systems to study their production in subsequent conversations. This literature has revealed considerable semantic competences in great apes, but no evidence for a corresponding grammatical ability, at least in production. No ape has ever created a sentence with an underlying causal structure of agency and patienthood. A second approach has been to study natural communication in primates and other animals. Here, there is intermittent evidence of compositionality, for example, a capacity to perform operations on semantic units, but again no evidence for an ability to refer to the causal structure of events. Future research will have to decide whether primates and other animals are simply unable to see the world as casually structured the way humans do, or whether they are just unable to communicate causal structures to others. This article is categorized under:Cognitive Biology > Evolutionary Roots of CognitionComputer Science and Robotics > Artificial IntelligenceLinguistics > Evolution of Language [ABSTRACT FROM AUTHOR]

This paper discusses part of speech (PoS) tagging for Arabic prepositions. Arabic has a number of predefined sets of particles such as particles of Nasb, particles of Jazm, particles of Jarr (also called prepositions), etc. Each set has a particular role in the context in which it appears. In general, PoS is the process of assigning a tag for each word (e.g. name, verb, particle, etc.) based on the context. In fact, PoS is a beneficial tool for many natural language processing (NLP) toolkits. For instance, it is used in syntactic parsing to validate the grammar of the sentence in question. It is also beneficial to understand the required meaning via textual analysis for further processing in search engines. Many other language processing applications utilize PoS such as machine translation, speech synthesis, speech recognition, diacritization, etc. Hence, the performance quality of many NLP applications depends on the accuracy of outputs of the used tagging system. Hence, this study examines the Stanford tagger to explore its tag set in the text under examination and its performance for tagging Arabic prepositions. This study also discusses the weaknesses of the Stanford tagger, as it does not handle the merging case when a preposition joins with an adjacent word to form one single word. Another concern of the Stanford tagger is that it gives a unique tag for different particles such as Jarr and Jazm in terms of linguistic functions. Through our inductive study of prepositions in terms of linguistic functions such as Jazm and Istifham (interrogation), we did not note differences in tagging prepositions like “to” (إلى )and “in” (في .)Other prepositions are also difficult to distinguish unless they are contextualized; these include “until” (حتى )and “except” (عدا .)This shows that this tagging system is inaccurate and the need for keeping up with tagging-related systems is vital, hence is the significance of our research. In this work, we used the Holy Quran to identify the performance of the Stanford System in tagging prepositions in the Quran. This work encourages more research on tagging other Arabic prepositions to explore the compatibility of tagging symbols employed in the Stanford System and prepositions used in the Arabic language, in general. [ABSTRACT FROM AUTHOR]

We study the computational power of parsing expression grammars (PEGs). We begin by constructing PEGs with unexpected behaviour, and surprising new examples of languages with PEGs, including the language of palindromes whose length is a power of two, and a binary-counting language. We then propose a new computational model, the scaffolding automaton , and prove that it exactly characterises the computational power of parsing expression grammars (PEGs). Several consequences will follow from this characterisation: (1) we show that PEGs are computationally "universal", in a certain sense, which implies the existence of a PEG for a P-complete language; (2) we show that there can be no pumping lemma for PEGs; and (3) we show that PEGs are strictly more powerful than online Turing machines which do o (n / (log ⁡ n) 2) steps of computation per input symbol. [ABSTRACT FROM AUTHOR]

With the constantly generation of process data in industries, process knowledge reuse and learning from process dataset has shown promising potential in machining process planning. However, existing methods cannot effectively extract different granularity process intents, and thus the process data cannot be effectively utilized. In this paper, an effective process design intent inference method of process data via integrating deep learning and grammar parsing is proposed. First, based on the projection of cutter location segments, an association approach between machining operations and machining features is proposed to extract the process intent of each machining operation. Then, a deep learning based working step process intent sequence decision-making model is proposed to estimate the probability distributions of alternative working step process intents at each time. Moreover, according to the working step process intent sequences of existing parts in an industry, the process knowledge And-Or graph (PK-AOG) is constructed by introducing the probabilistic grammar graph model. Finally, the optimal process intents of each working step are jointly obtained based on grammar parsing by taking the PK-AOG as a guide. In the experiments, the effectiveness of our approach is validated by developing a prototype system, and the results show that our approach is practical in process intents extraction. [ABSTRACT FROM AUTHOR]

We present algorithms for extracting Hyperedge Replacement Grammar (HRG) rules from a graph along with a vertex order. Our algorithms are based on finding a tree decomposition of smallest width, relative to the vertex order, and then extracting one rule for each node in this structure. The assumption of a fixed order for the vertices of the input graph makes it possible to solve the problem in polynomial time, in contrast to the fact that the problem of finding optimal tree decompositions for a graph is NP-hard. We also present polynomial-time algorithms for parsing based on our HRGs, where the input is a vertex sequence and the output is a graph structure. The intended application of our algorithms is grammar extraction and parsing for semantic representation of natural language. We apply our algorithms to data annotated with Abstract Meaning Representations and report on the characteristics of the resulting grammars. [ABSTRACT FROM AUTHOR]

It is a major open problem whether the (min, +)-product of two n × n matrices has a truly subcubic (i.e., O(n3-ε) for ε > 0) time algorithm; in particular, since it is equivalent to the famous all-pairs-shortest-paths problem (APSP) in n-vertex graphs. Some restrictions of the (min,+)-product to special types of matrices are known to admit truly subcubic algorithms, each giving rise to a special case of APSP that can be solved faster. In this paper we consider a new, different, and powerful restriction in which all matrix entries are integers and one matrix can be arbitrary, as long as the other matrix has "bounded differences" in either its columns or rows, i.e., any two consecutive entries differ by only a small amount. We obtain the first truly subcubic algorithm for this bounded-difference (min, +)-product (answering an open problem of Chan and Lewenstein). Our new algorithm, combined with a strengthening of an approach of Valiant for solving context-free grammar parsing with matrix multiplication, yields the first truly subcubic algorithms for the following problems: language edit distance (a major problem in the parsing community), RNA folding (a major problem in bioinformatics), and optimum stack generation (answering an open problem of Tarjan). [ABSTRACT FROM AUTHOR]

Highlights • The parse of lian involves reusing the structure projected by a scalar implicature. • Dou is an intensifier-like adverb used to reinforce the illocutionary force of the sentence containing lian...dou. • The parse of Dou suggests that the alternatives projected by a scalar implicature are true in the relevant context. Abstract This paper deals with the puzzling Chinese verb doubling construction in the schema of lian...dou (verb doubling lian...dou construction, VDLD) from a parsing perspective. Within the framework of Dynamic Syntax (Kempson et al., 2001; Cann et al., 2005) which allows the interaction between structural, semantic and pragmatic information, it is shown that VDLD can receive a straightforward explanation on the assumption that the construction is licensed by an explicit or implicit context. Specifically, it is argued that (i) the first verb marked by lian is a topicalized focus, whose parse involves reusing the structure projected by a scalar implicature; (ii) dou is an intensifier-like adverb, whose parse suggests that the alternatives projected by a scalar implicature should be true in the relevant context. [ABSTRACT FROM AUTHOR]

Evidence from two experiments reveals that in Chamorro, a verb-first language, the comprehension of relative clauses (RCs) is sensitive to the order of the RC with respect to the head. Unlike most other languages, Chamorro allows both postnominal and prenominal RCs, so it is possible to compare how the two types are processed within the same language. Moreover, Chamorro is a small language whose speakers do not fit the typical profile of participants in cognitive science experiments. We found that RC comprehension is affected by the relative order of RC and head, and by other language-specific factors. However, we also found new support for a subject gap advantage in all RC types. This advantage emerged in early response measures and was reinforced in postnominal RCs, but often outcompeted in prenominal RCs by other pressures. We frame this competition in terms of a model in which grammatical licensing requirements play a key role in comprehension. [ABSTRACT FROM AUTHOR]

The usage of context clues to determine the meaning of target nonsense words (emphasized made-up words) was examined to determine the types and structure of context clues people use in reading. Specifically, participants were provided with sample sentences and were then asked to define a target nonsense word. Second, they reported a specific word from the sentence that was used as a context clue to help them define the emphasized nonsense word. These words were then analyzed to determine how context clues impacted interpretation of an unknown word by exploring the combination of reported words and nonsense words parts of speech (i.e., noun, verb, etc.). For noun target words, verb and adverb context clues were used most frequently and for verb context clues, noun context clues were used most frequently. These findings suggest the application of semantic bias in processing, or that the structure and meaning of the sentence predisposes readers to specific interpretations. However, for adjective context clues, noun context clues were used most frequently, utilizing the principle of right association (i.e., using the closest word to the unknown word in order to help discern meaning). [ABSTRACT FROM AUTHOR]

Background: The current study explored the effect of implicit prosody on syntactic parsing in the silent reading of an ambiguous double prepositional phrase (PP) construction in Hebrew by employing the Implicit Prosody Hypothesis test (Fodor, ). Method: The parsing preferences of the construction in silent reading were tested and compared to those in a reading aloud study (Webman‐Shafran & Fodor, ) containing the same experimental material. Results: The parsing results were remarkably similar. Conclusions: It is suggested that implicit prosody was responsible for syntactic ambiguity resolution preferences in silent reading in the current study in the same way as overt prosody in reading aloud in Webman‐Shafran and Fodor ( ). This study supports the assumption that reading prosody is projected in silent reading and affects comprehension. Implications: The contribution of implicit prosody to the reading process may have important implications for reading instruction in FLA, SLA and reading disorder intervention programs. [ABSTRACT FROM AUTHOR]

Abstract: Right node raising sentences (RNR) have proved to be difficult for modern syntactic theory to account in an explanatory fashion. In this paper I argue that the reason for this difficulty is that RNR cannot be fully analyzed as a construction independent of online parsing. I argue against current and possible grammatical analyses of the construction and posit that the interpretation of the shared material in the first conjunct is effectively illusory. That is, the interpretive relation between the shared material in RNR and the gap position in the first conjunct is not encoded in the offline representation of the construction, but rather is only captured via a transitory online parsing operation. This analysis has consequences for the relation between the grammar and the parser as well the limits of grammatical relations. [ABSTRACT FROM AUTHOR]

This paper investigates whether attachment ambiguity preference attested in psycholinguistic literature can be correctly predicted, utilizing memory based metrics developed by Graf et al. (2017). Two different types of attachment ambiguity in Korean, the dative argument attachment ambiguity and the relative clause attachment ambiguity, are mainly tested. Furthermore, in order to examine whether the Minimalist Grammar Parsing Model can predict the broad human sentence processing effects, the work in the previous literature in Graf et al. (2017) were tested together. While none of the single metrics made the correct predictions, the combination of metrics based on tenure and size could predict the preferences of all different kinds of constructions reported in psycholinguistic studies. This suggests that human sentence processing effect cannot be understood by a single element. The well-selected metrics in this paper can tell us what kind of structural complexity are related to processing sentences. [ABSTRACT FROM AUTHOR]

Conjunctions have different interpretations: they eliminate redundancies: “María se bañó y se peinó” (Maria bathed and she combed her hair), unite different ideas: “Hoy llovió y no fui a corer” (Today it rained and I did not go to run) and use of lists: “Eran Alma, Edith y Omar” (They were Alma, Edith and Omar). Conjunctions take different semantic contexts. We understand each other because of the common sense despite expressing ourselves incorrectly from the standpoint of semantics, but for a computer it is difficult. In order to “understand” the sentences, the machine must solve semantics problems; this article exposes one of these problems. ANACONJ is an algorithm of pattern recognition of texts, which uses rules and syntactic patterns that analyze each word of a sentence in a phrase, identifying those sentences with conjunctions to build a semantic tree of the sentence where the conjunction connects words (nouns, verbs, etc.) according to their meaning. ANACONJ could be used as a teaching Spanish software tool and as an app for a service robot too. [ABSTRACT FROM AUTHOR]

Unambiguous conjunctive grammars with 1 nonterminal symbol are shown to be strictly weaker than the grammars with 2 nonterminal symbols, which are in turn strictly weaker that the grammars with 3 or more nonterminal symbols. This hierarchy is established by considering grammars over a one-symbol alphabet, for which it is shown that 1-nonterminal grammars describe only regular languages, 2-nonterminal grammars describe some non-regular languages, but all of them are in a certain sense sparse, whereas 3-nonterminal grammars may describe some non-regular languages of non-zero density. It is also proved that one can test a 2-nonterminal grammar for equivalence with a regular language, whereas the equivalence between a pair of 2-nonterminal grammars is undecidable. [ABSTRACT FROM AUTHOR]

This article describes a left-corner parser implemented within a cognitively and neurologically motivated distributed model of memory. This parser's approach to syntactic ambiguity points toward a tidy account both of surprisal effects and of locality effects, such as the parsing breakdowns caused by center embedding. The model provides an algorithmic-level (Marr, 1982) account of these breakdowns: The structure of the parser's memory and the nature of incremental parsing produce a smooth degradation of processing accuracy for longer center embeddings, and a steeper degradation when they are nested, in line with recall observations by Miller and Isard (1964) and speed-accuracy trade-off observations by McElree et al. (2003). Modeling results show that this effect is distinct from the effects of ambiguity and exceeds the effect of mere sentence length. [ABSTRACT FROM AUTHOR]

Computational text-level discourse analysis mostly happens within Rhetorical Structure Theory (RST), whose structures have classically been presented as constituency trees, and relies on data from the RST Discourse Treebank (RST-DT); as a result, the RST discourse parsing community has largely borrowed from the syntactic constituency parsing community. The standard evaluation procedure for RST discourse parsers is thus a simplified variant of PARSEVAL, and most RST discourse parsers use techniques that originated in syntactic constituency parsing. In this article, we isolate a number of conceptual and computational problems with the constituency hypothesis. We then examine the consequences, for the implementation and evaluation of RST discourse parsers, of adopting a dependency perspective on RST structures, a view advocated so far only by a few approaches to discourse parsing. While doing that, we show the importance of the notion of headedness of RST structures. We analyze RST discourse parsing as dependency parsing by adapting to RST a recent proposal in syntactic parsing that relies on head-ordered dependency trees, a representation isomorphic to headed constituency trees. We show how to convert the original trees from the RST corpus, RST-DT, and their binarized versions used by all existing RST parsers to head-ordered dependency trees. We also propose a way to convert existing simple dependency parser output to constituent trees. This allows us to evaluate and to compare approaches from both constituent-based and dependency-based perspectives in a unified framework, using constituency and dependency metrics. We thus propose an evaluation framework to compare extant approaches easily and uniformly, something the RST parsing community has lacked up to now. We can also compare parsers’ predictions to each other across frameworks. This allows us to characterize families of parsing strategies across the different frameworks, in particular with respect to the notion of headedness. Our experiments provide evidence for the conceptual similarities between dependency parsers and shift-reduce constituency parsers, and confirm that dependency parsing constitutes a viable approach to RST discourse parsing. [ABSTRACT FROM AUTHOR]

This paper studies parsing as a practice used in mobile instruction. The findings build on ethnomethodological conversation analysis and on observations made on video data that have been collected from three settings: skiing, driving a car and flying a plane. In the data, novice learners are instructed by more experienced instructors to accomplish various mobile tasks. The paper shows how instructors use parsing to guide learners to carry out, step-by-step, the sub-actions that the ongoing mobile task (e.g. turning, landing) is composed of. The paper argues that parsing is a practice employed by instructors to highlight the sub-actions of a mobile task. Instructors may also use parsing to orient learners to emergent problems to do with the timing, quality and order of the sub-actions in the performance of a complex mobile task. Finally, the paper shows that sometimes there is not enough time to parse an ongoing task, in which case the parsing can be carried out afterwards. [ABSTRACT FROM AUTHOR]

Grammars with contexts are an extension of context-free grammars equipped with operators for referring to the left and the right contexts of a substring being defined. These grammars are notable for still having a cubic-time parsing algorithm, as well as for being able to describe some useful syntactic constructs, such as declaration before use. It is proved in this paper that every language described by a grammar with contexts can be recognized in deterministic linear space. [ABSTRACT FROM AUTHOR]

We describe a conversion of the syntactically annotated part of the Slovak National Corpus into the annotation scheme known as Universal Dependencies. Only a small subset of the data has been converted so far; yet it is the first Slovak treebank that is publicly available for research. We list a number of research projects in which the dataset has been used so far, including the first parsing results. [ABSTRACT FROM AUTHOR]

Multiword expressions (MWEs) are a class of linguistic forms spanning conventional word boundaries that are both idiosyncratic and pervasive across different languages. The structure of linguistic processing that depends on the clear distinction between words and phrases has to be re-thought to accommodate MWEs. The issue of MWE handling is crucial for NLP applications, where it raises a number of challenges. The emergence of solutions in the absence of guiding principles motivates this survey, whose aim is not only to provide a focused review of MWE processing, but also to clarify the nature of interactions between MWE processing and downstream applications. We propose a conceptual framework within which challenges and research contributions can be positioned. It offers a shared understanding of what is meant by "MWE processing," distinguishing the subtasks of MWE discovery and identification. It also elucidates the interactions between MWE processing and two use cases: Parsing and machine translation. Many of the approaches in the literature can be differentiated according to howMWE processing is timed with respect to underlying use cases. We discuss how such orchestration choices affect the scope of MWE-aware systems. For each of the two MWE processing subtasks and for each of the two use cases, we conclude on open issues and research perspectives. [ABSTRACT FROM AUTHOR]

Recent work has demonstrated that explicit error detection relies on a neural evidence accumulation process that can be traced in the human electroencephalogram (EEG). Here, we sought to establish the impact of natural aging on this process by recording EEG from young (18–35 years) and older adults (65–88 years) during the performance of a Go/No-Go paradigm in which participants were required to overtly signal their errors. Despite performing the task with equivalent accuracy, older adults reported substantially fewer errors, and the timing of their reports were both slower and more variable. These behavioral differences were linked to three key neurophysiological changes reflecting distinct parameters of the error detection decision process: a reduction in medial frontal delta/theta (2–7 Hz) activity, indicating diminished top-down input to the decision process; a slower rate of evidence accumulation as indexed by the rate of rise of a centro-parietal signal, known as the error positivity; and a higher motor execution threshold as indexed by lateralized beta-band (16–30 Hz) activity. Our data provide novel insight into how the natural aging process affects the neural underpinnings of error detection. [ABSTRACT FROM AUTHOR]

A controlled reading experiment reveals that stress-based linguistic rhythm impinges on syntactic ambiguity resolution in silent and oral reading. The results suggest that, at points of syntactic underspecification, the accruing prosodic representation may affect even the earliest stages of structure building, viz. the analysis of syntactic features of an ambiguous word. Such an effect remains inexplicable in the context of (psycho-)linguistic theories that assume a strictly unidirectional relationship between syntactic and phonological processes, the latter merely interpreting the conditions the syntactic component imposes on it. Here, a performance compatible grammar in the framework of Optimal Parsing is presented that is capable of capturing the reading data. The model integrates syntactic parsing and prosodification in reading and predicts that, at points of syntactic indetermination, weak prosodic constraints alone may guide syntactic structure assignment. This suggests a bidirectional relationship between syntax and phonology in grammar and processing while, at the same time, confirming a tight coupling of language production and comprehension. [ABSTRACT FROM AUTHOR]

Brain–machine interfaces (BMIs) define new ways to interact with our environment and hold great promise for clinical therapies. Motor BMIs, for instance, re-route neural activity to control movements of a new effector and could restore movement to people with paralysis. Increasing experience shows that interfacing with the brain inevitably changes the brain. BMIs engage and depend on a wide array of innate learning mechanisms to produce meaningful behavior. BMIs precisely define the information streams into and out of the brain, but engage wide-spread learning. We take a network perspective and review existing observations of learning in motor BMIs to show that BMIs engage multiple learning mechanisms distributed across neural networks. Recent studies demonstrate the advantages of BMI for parsing this learning and its underlying neural mechanisms. BMIs therefore provide a powerful tool for studying the neural mechanisms of learning that highlights the critical role of learning in engineered neural therapies. [ABSTRACT FROM AUTHOR]

In a series of three experiments, we use children’s noun learning as a probe into their syntactic knowledge as well as their ability to deploy this knowledge, investigating how the predictions children make about upcoming syntactic structure change as their knowledge changes. In the first two experiments, we show that children display a developmental change in their ability to use a noun’s syntactic environment as a cue to its meaning. We argue that this pattern arises from children’s reliance on their knowledge of verbs’ subcategorization frame frequencies to guide parsing, coupled with an inability to revise incremental parsing decisions. We show that this analysis is consistent with the syntactic distributions in child-directed speech. In the third experiment, we show that the change arises from predictions based on verbs’ subcategorization frame frequencies. [ABSTRACT FROM AUTHOR]

Previous studies concluded that despite the parser's eagerness to resolve filler-gap dependencies, in island configurations it prefers to posit late grammatical gaps over early ungrammatical ones. This study investigates the possibility o f resolving filler-gap dependencies inside Hebrew islands. We investigated the acceptability of resumptive pronouns (RPs) in two islands and the sensitivity of on-line dependency formation to the status of those RPs. Results revealed a filled-gap effect inside the island that allows RPs but not inside the one that prohibits them. This suggests that active dependency formation can proceed inside islands, and that when processing dependencies with islands, the Hebrew parser prefers an early RP over a later gap. [ABSTRACT FROM AUTHOR]

In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed model globally optimizes argument component types and argumentative relations using Integer Linear Programming. We show that our model significantly outperforms challenging heuristic baselines on two different types of discourse. Moreover, we introduce a novel corpus of persuasive essays annotated with argumentation structures. We show that our annotation scheme and annotation guidelines successfully guide human annotators to substantial agreement. [ABSTRACT FROM AUTHOR]

We explore the concept of hybrid grammars, which formalize and generalize a range of existing frameworks for dealing with discontinuous syntactic structures. Covered are both discontinuous phrase structures and non-projective dependency structures. Technically, hybrid grammars are related to synchronous grammars, where one grammar component generates linear structures and another generates hierarchical structures. By coupling lexical elements of both components together, discontinuous structures result. Several types of hybrid grammars are characterized. We also discuss grammar induction from treebanks. The main advantage over existing frameworks is the ability of hybrid grammars to separate discontinuity of the desired structures from time complexity of parsing. This permits exploration of a large variety of parsing algorithms for discontinuous structures, with different properties. This is confirmed by the reported experimental results, which show a wide variety of running time, accuracy, and frequency of parse failures. [ABSTRACT FROM AUTHOR]

To deal with the parameter estimation problem in multi-function radars( MFR) based on stochastic context-free grammar( SCFG) model,this paper developed a new method of MFR parameter estimation problem based on Earley parsing called EIO algorithm on the basis of traditional inside-outside( IO) algorithm and viterbi-score( VS) algorithm. This method pre-processed the intercepted radar data by combining IO algorithm with Earley parsing to handle arbitrary grammar production rules. It utilized the EIO algorithm to realize the learning of grammatical production rules probabilities and MFR parameter estimation. Theoretical analysis and simulation results show that the modified algorithm can reduce the computation complexity,memory complexity and running time while keeping the same level of estimation accuracy,validates the correctness and effectiveness of this method. [ABSTRACT FROM AUTHOR]

A growing body of research has investigated bilingual sentence processing. How to account for differences in native (L1) and non-native (L2) processing is controversial. Some explain L1/L2 differences in terms of different parsing mechanisms, and the hypothesis that L2 learners adopt ‘shallow’ parsing has received considerable attention. Others assume L1/L2 processing is similar, and explain L1/L2 differences in terms of capacity-based limitations being exceeded during L2 processing. More generally, the role that working memory plays in language acquisition and processing has garnered increasing interest. Based on research investigating L2 sentence processing, I claim that a primary source of L1/L2 differences lies in the ability to retrieve information constructed during sentence processing from memory. In contrast to describing L1/L2 differences in terms of shallow parsing or capacity limitations, I argue that L2 speakers are more susceptible to retrieval interference when successful comprehension requires access to information from memory. [ABSTRACT FROM AUTHOR]

This paper revisits the conclusion of our previous work regarding the dominance of meaning in the competition between rhythmic parsing and linguistic parsing. We played five-note rhythm patterns in which each sound is a spoken word of a five-word sentence. We asked listeners to indicate the starting point of the rhythm while disregarding which word would normally be heard as the first word of the sentence. In four studies, we varied task demands by introducing differences in rhythm complexity, rhythm ambiguity, rhythm pairing, and semantic coherence. We found that task complexity affects the dominance of meaning. We therefore amend our previous conclusion: when processing resources are taxed, listeners do not always primarily attend to meaning; instead, they primarily attend to the aspect of the pattern (rhythm or meaning) that is more salient. [ABSTRACT FROM AUTHOR]

The article discusses the use of dynamic syntax (DS) as a pragmatic approach to language parsing. Topics covered include how coherent interaction between participants in a multiparty conversation impose constraints, an approach to language via dialogues, and the traditional perspective on linguistics. Also mentioned are the complexity of natural language's syntax, the translation of natural language syntax into mathematical notation, and the computational paradigm provided by proof search.

The article discusses the dynamic syntax (DS) approach to embedding an account of linguistic behavior in a theory of action while considering natural languages as formal systems. Topics covered include the use of analysis trees, computational actions that operate on trees, and definite clause grammars (DCG). Also mentioned are computational approaches to parsing, linguistic theory's emphasis on incremental processing, and gameboard theory.

Research investigating the brain basis of language comprehension has associated the left anterior temporal lobe ( ATL) with sentence-level combinatorics. Using magnetoencephalography ( MEG), we test the parsing strategy implemented in this brain region. The number of incremental parse steps from a predictive left-corner parsing strategy that is supported by psycholinguistic research is compared with those from a less-predictive strategy. We test for a correlation between parse steps and source-localized MEG activity recorded while participants read a story. Left-corner parse steps correlated with activity in the left ATL around 350-500 ms after word onset. No other correlations specific to sentence comprehension were observed. These data indicate that the left ATL engages in combinatoric processing that is well characterized by a predictive left-corner parsing strategy. [ABSTRACT FROM AUTHOR]

This article traces the history of Latin parsing grammars from Late Antiquity up to the 14th century, focusing on the group of texts with the incipit Dominus quae pars. These grammars circulating mainly north of the Alps were intended to be studied at the elementary and intermediate levels of education following the study of the Donatus minor. By asking questions about a chosen headword of each part of speech in turn, the parsing manuals offered a technique which allowed the pupil to put into practice what he had already learnt and the teacher to focus on the information he considered as relevant, including different aspects of morphology, semantics, etymology, prosody or accentuation. A number of novelties introduced into the theoretical grammars also filtered down to the lower levels of teaching. Thus, when a section on syntax began to be incorporated into pedagogical grammars in the 12th century, some syntactical concepts also entered into parsing grammars. From the 13th century onwards, elements of Aristotelian logic and physics were also integrated into the theory of the parts of speech and their syntax in the Dominus quae pars texts. [ABSTRACT FROM AUTHOR]

Purpose: The present study tested whether (and how) language treatment changed online sentence processing in individuals with aphasia. Method: Participants with aphasia (n = 10) received a 12-week program of Treatment of Underlying Forms (Thompson & Shapiro, 2005) focused on production and comprehension of passive sentences. Before and after treatment, participants performed a sentence-picture matching task with active and passive sentences as eye movements were tracked. Twelve age-matched controls also performed the task once each. Results: In the age-matched group, eye movements indicated agent-first predictive processing after hearing the subject noun, followed by rapid thematic reanalysis after hearing the verb form. Pretreatment eye movements in the participants with aphasia showed no predictive agent-first processing, and more accurate thematic analysis in active compared to passive sentences. After treatment, which resulted in improved offline passive sentence production and comprehension, participants were more likely to respond correctly when they made agent-first eye movements early in the sentence, showed equally reliable thematic analysis in active and passive sentences, and were less likely to use a spatially based alternative response strategy. Conclusions: These findings suggest that treatment focused on improving sentence production and comprehension supports the emergence of more normal-like sentence comprehension processes. [ABSTRACT FROM AUTHOR]

Elementary sentences containing the quantificational determiner some seem to be ambiguous between a 'weak' existential meaning ∃ and a 'strengthened' some but not all meaning ∃+. The strengthened meaning is commonly assumed to be the output of a general enrichment mechanism, call it G (for 'global'), that applies to the weak meaning of the sentence: G (∃) = ∃+. The application of G has been shown to come with a processing cost (e.g. Bott & Noveck 2004). We used a self-paced reading task together with offline comprehension questions to investigate the interpretation of sentences containing some when embedded inside a disjunction, a position that G cannot access. Our findings suggest (i) that the strengthened meaning ∃+ is available in embedded positions, suggesting that a mechanism of local strengthening L must be available: L (∃) = ∃+, (ii) that local enrichment can be facilitated by global pragmatic pressures (Chierchia et al. 2008; Mayr & Romoli 2014), (iii) that subjects can be quickly trained to systematically prefer one of G or L to the other, (iv) that application of L, like the application of G, comes with a processing cost. We highlight consequences of our findings for debates about the characterization of enrichment mechanisms, focusing on the relation between G and L . [ABSTRACT FROM AUTHOR]

A controlled reading experiment reveals that stress-based linguistic rhythm impinges on syntactic ambiguity resolution in silent and oral reading. The results suggest that, at points of syntactic underspecification, the accruing prosodic representation may affect even the earliest stages of structure building, viz. the analysis of syntactic features of an ambiguous word. Such an effect remains inexplicable in the context of (psycho-)linguistic theories that assume a strictly unidirectional relationship between syntactic and phonological processes, the latter merely interpreting the conditions the syntactic component imposes on it. Here, a performance compatible grammar in the framework of Optimal Parsing is presented that is capable of capturing the reading data. The model integrates syntactic parsing and prosodification in reading and predicts that, at points of syntactic indetermination, weak prosodic constraints alone may guide syntactic structure assignment. This suggests a bidirectional relationship between syntax and phonology in grammar and processing while, at the same time, confirming a tight coupling of language production and comprehension. [ABSTRACT FROM AUTHOR]

We describe the investigation of automatic annotation of text with pictures, where knowledge extraction uses dependency parsing. Annotation of text with pictures, a form of knowledge visualization, can assist understanding. The problem statement is, given a corpus of images and a short passage of text, extract knowledge (or concepts), and then display that knowledge in pictures along with the text to help with understanding. A proposed solution framework includes a component to extract document concepts, a component to match document concepts with picture metadata, and a component to produce an amalgamated output of text and pictures. A proof-of-concept application based on the proposed framework provides encouraging results [ABSTRACT FROM AUTHOR]

The Tanzanian Bantu language Rangi exhibits a comparatively and typologically unusual word order alternation in the future tense. Whilst declarative main clauses exhibit post-verbal auxiliary placement, the auxiliary appears pre-verbally in wh-questions, sentential negation, relative clauses, cleft constructions and subordinate clauses. This paper examines this alternation from the perspective of Dynamic Syntax ( Cann et al., 2005; Kempson et al., 2001 ). Dynamic Syntax (DS) is a parsing-oriented framework which aims to capture the way in which meaning is established incrementally as a result of lexical input encountered in context. The paper presents a unified analysis of this construction found in Rangi, locating it within the wider workings of the language. It shows that this seemingly idiosyncratic constituent order is in fact predictable on the basis of a general constraint operative in the DS framework which prohibits the co-occurrence of more than one unfixed node, thereby also confirming the claim of Dynamic Syntax to constitute a grammar framework rather than merely a parsing device. [ABSTRACT FROM AUTHOR]

In the last decade, various restricted classes of non-projective dependency trees have been proposed with the goal of achieving a good tradeoff between parsing efficiency and coverage of the syntactic structures found in natural languages. We perform an extensive study measuring the coverage of a wide range of such classes on corpora of 30 languages under two different syntactic annotation criteria. The results show that, among the currently known relaxations of projectivity, the best tradeoff between coverage and computational complexity of exact parsing is achieved by either 1-endpoint-crossing trees or MHk trees, depending on the level of coverage desired. We also present some properties of the relation of MHk trees to other relevant classes of trees. [ABSTRACT FROM AUTHOR]

The speech signal conveys information on different time scales from short (20–40 ms) time scale or segmental, associated to phonological and phonetic information to long (150–250 ms) time scale or supra segmental, associated to syllabic and prosodic information. Linguistic and neurocognitive studies recognize the phonological classes at segmental level as the essential and invariant representations used in speech temporal organization. In the context of speech processing, a deep neural network (DNN) is an effective computational method to infer the probability of individual phonological classes from a short segment of speech signal. A vector of all phonological class probabilities is referred to as phonological posterior . There are only very few classes comprising a short term speech signal; hence, the phonological posterior is a sparse vector. Although the phonological posteriors are estimated at segmental level, we claim that they convey supra-segmental information. Specifically, we demonstrate that phonological posteriors are indicative of syllabic and prosodic events. Building on findings from converging linguistic evidence on the gestural model of Articulatory Phonology as well as the neural basis of speech perception, we hypothesize that phonological posteriors convey properties of linguistic classes at multiple time scales, and this information is embedded in their support (index) of active coefficients. To verify this hypothesis, we obtain a binary representation of phonological posteriors at the segmental level which is referred to as first-order sparsity structure; the high-order structures are obtained by the concatenation of first-order binary vectors. It is then confirmed that the classification of supra-segmental linguistic events, the problem known as linguistic parsing , can be achieved with high accuracy using a simple binary pattern matching of first-order or high-order structures. [ABSTRACT FROM AUTHOR]

The present study demonstrates the existence in Wandala (Central Chadic) of two inflectional markers which, although they change the form of the word, are not word-formation means but rather sentence-formation means. While neither of the forms indicates any specific semantic relation, they both enable the listener to parse the sentence into units that can undergo further analysis and allow for inferences about a large number of semantic relations within the clause and within the sentence. The types of inflectional marking described in this study are unrelated to the dichotomy of head marking and dependent marking. Although this study is based on data from a single language, it has implications for the typology of coding means and for theories of clausal structures. [ABSTRACT FROM AUTHOR]

In this article, we introduce the effect of “constructional contamination”. In constructional contamination, a subset of the instances of a target construction deviate in their realization, due to a superficial resemblance they share with instances of a contaminating construction. We claim that this contaminating effect bears testimony to the hypothesis that language users do not always execute a full parse while interpreting and producing sentences. Instead, they may rely on what has been called “shallow parsing”, i. e., chunking the utterances into large, unanalyzed exemplars that may extend across constituent borders. We propose several measures to quantify constructional contamination in corpus data. To evaluate these measures, the Dutch partitive genitive is taken under scrutiny as a target construction of constructional contamination. In this case study, it is shown that neighboring constructions play a crucial role in determining the presence or absence of the -s suffix among instances of the partitive genitive. The different measures themselves, however, are not construction- specific, and can readily be used to track constructional contamination in other case studies as well. [ABSTRACT FROM AUTHOR]

This contribution investigates the syntactic conceptions of, and the diagramming system introduced by, the American grammarian Stephen Watkins Clark (1810-1901), who introduced the first comprehensive syntactic diagramming system. The structure of the English sentence is illustrated by agglutinated 'bubbles' expressing the relations between words by the means of their relative position. The sentence consists of two or three horizontally aligned bubbles containing words that are called principal elements. These principal elements can be complemented with adjunct elements, that appear in bubbles attached below them. For grammatical words the conventions differ depending on whether the grammatical word is a preposition or a conjunction. Coordination is never named as such, but there is an orthogonal abstract relation that connects elements performing the same role in a "compound" construction. The system allows recursivity in two different ways: by wrapping bubbles into other bubbles, thus following a mereological logic (i.e., partwhole relations) close to IC analysis or by hierarchically aggregating bubbles that resemble dependency trees. Clark's conceptions thus prefigure modern graphical formalizations. [ABSTRACT FROM AUTHOR]