scholarly journals How do people interpret implausible sentences?

2021 ◽  
Author(s):  
Zhenguang Garry Cai ◽  
Nan Zhao ◽  
Martin John Pickering
Keyword(s):  
Semantic Analysis ◽  
Syntactic Analysis ◽  
Structural Priming ◽  
Comprehension Question ◽  
Double Object ◽  
Prepositional Object ◽  
Do So

People sometimes interpret implausible sentences non-literally, for example treating The mother gave the candle the daughter as meaning the daughter receiving the candle. But how do they do so? We contrasted a nonliteral syntactic analysis account, according to which people compute a syntactic analysis appropriate for this nonliteral meaning, with a nonliteral semantic analysis account, according to which they arrive at this meaning via purely semantic analysis. The nonliteral syntactic but not semantic reanalysis account postulates that people consider not only a literal-but-implausible double-object (DO) analysis in comprehending The mother gave the candle the daughter, but also a nonliteral-but-plausible prepositional-object (PO) analysis (i.e., including to before the daughter). In three structural priming experiments, participants heard a plausible or implausible DO or PO prime sentence. They then answered a comprehension question first or described a picture of a dative event first. In line with the nonliteral syntactic analysis account, priming was reduced following implausible than plausible sentences and following nonliterally than literally-interpreted implausible sentences. We argue that comprehenders project a plausible analysis before they have encountered the whole sentence (e.g., a PO analysis at the candle for The mother gave the candle the daughter) and that this analysis is often maintained even if it turns to be incorrect.

scholarly journals The role of L1 and L2 frequency in cross-linguistic structural priming: An artificial language learning study

2021 ◽  
pp. 1-12
Author(s):  
Merel Muylle ◽  
Sarah Bernolet ◽  
Robert J. Hartsuiker
Keyword(s):  
Language Learning ◽  
Structural Priming ◽  
Artificial Language ◽  
Double Object ◽  
Frequency Effects ◽  
Artificial Language Learning ◽  
Prepositional Object ◽  
Biased Language ◽  
L1 And L2

Abstract We investigated L1 and L2 frequency effects in the sharing of syntax across languages (reflected in cross-linguistic structural priming) using an artificial language (AL) paradigm. Ninety-six Dutch speakers learned an AL with either a prepositional-object (PO) dative bias (PO datives appeared three times as often as double-object [DO] datives) or a DO dative bias (DOs appeared three times as often as POs). Priming was assessed from the AL to Dutch (a strongly PO-biased language). There was weak immediate priming for DOs, but not for POs in both bias conditions. This suggests that L1, but not AL, frequency influenced immediate priming. Furthermore, the DO bias group produced 10% more DOs in Dutch than the PO bias group, showing that cumulative priming was influenced by AL frequency. We discuss the different effects of L1 and AL frequency on cross-linguistic structural priming in terms of lexicalist and implicit learning accounts.

scholarly journals Implicit and Explicit Memory Factors in Cumulative Structural Priming

2017 ◽  
Vol 3 (1) ◽  
Author(s):  
Timothy J. Kutta ◽  
Michael P. Kaschak ◽  
Angela Porcellini ◽  
John L. Jones
Keyword(s):  
Explicit Memory ◽  
Memory Effects ◽  
Structural Priming ◽  
Double Object ◽  
Short Term ◽  
Memory Processes ◽  
Base Rates ◽  
Implicit And Explicit Memory ◽  
Prepositional Object ◽  
Implicit And Explicit

Although researchers have argued that short-term structural priming is driven by both implicit and explicit memory processes, accounts of longer-term structural priming tend to focus on implicit memory processes. We explore this claim in five experiments. In the first two experiments, we replicate the finding that stronger cumulative structural priming is observed for the prepositional object (PO) construction than for the double object (DO) construction. The next three experiments explore the possibility that explicit memory effects may contribute to cumulative priming. The results of these experiments suggest that any explicit memory effects on cumulative priming are likely to be very weak. We conclude by conducting an analysis across all 5 experiments, and find that an examination of individual participants’ base rates of DO production helps to explain the circumstances under which cumulative priming for the DO and PO will be observed.

scholarly journals Are non-native structural preferences affected by native language preferences?

2012 ◽  
Vol 16 (4) ◽  
pp. 751-760 ◽  
Author(s):  
SUSANNA FLETT ◽  
HOLLY P. BRANIGAN ◽  
MARTIN J. PICKERING
Keyword(s):  
Native Language ◽  
Structural Priming ◽  
Double Object ◽  
Bilingual Speakers ◽  
Structural Preferences ◽  
Prepositional Object ◽  
Baseline Preference

A structural priming experiment investigated whether bilingual speakers’ processing of their non-native language (L2) depends entirely on their experience of L2, or whether it is also affected by their experience of the native language (L1). German-L1 and Spanish-L1 proficient speakers of English (and English-L1 controls) described pictures of dative events after reading unrelated sentences that had a Prepositional Object (PO) or Double Object (DO) structure. Participants in all three groups were more likely to produce DO descriptions after reading DO sentences than PO sentences. Crucially, Spanish-L1 speakers, whose L1 allows PO but not DO structures, showed the same pattern of priming as German-L1 speakers, whose L1 allows both structures. Additionally, the groups showed no difference in their baseline preference for DO structures. We suggest that in proficient bilinguals, processing in L2 is not affected by L1 experience and L1 preferences, and propose a model to account for our findings.

scholarly journals The role of L1 and L2 frequency in cross-linguistic structural priming: An artificial language learning study

2020 ◽  
Author(s):  
Merel Muylle ◽  
Bernolet Sarah ◽  
Robert Hartsuiker
Keyword(s):  
Language Learning ◽  
Structural Priming ◽  
Artificial Language ◽  
Double Object ◽  
Frequency Effects ◽  
Artificial Language Learning ◽  
Prepositional Object ◽  
Biased Language ◽  
L1 And L2

We investigated L1 and L2 frequency effects in the sharing of syntax across languages (reflected in cross-linguistic structural priming) using an artificial language (AL) paradigm. Ninety-six Dutch speakers learned an AL with either a prepositional-object (PO) dative bias (PO datives appeared three times as often as double-object [DO] datives) or a DO dative bias (DOs appeared three times as often as POs). Priming was assessed from the AL to Dutch (a strongly PO-biased language). There was weak immediate priming for DOs, but not for POs in both bias conditions. This suggests that L1, but not AL frequency influenced immediate priming. Furthermore, the DO bias group produced 10% more DOs in Dutch than the PO bias group, showing that cumulative priming was influenced by AL frequency. We discuss the different effects of L1 and AL frequency on cross-linguistic structural priming in terms of lexicalist and implicit learning accounts.

On the inherent semantic meaning of double object Latinate verbs in English in modern and historical perspective *

2013 ◽  
Vol 1 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Katarzyna Sówka-Pietraszewska
Keyword(s):  
Early Modern ◽  
Middle English ◽  
Historical Perspective ◽  
Time Span ◽  
Semantic Meaning ◽  
Double Object ◽  
Object Construction ◽  
Early Modern English ◽  
Prepositional Object ◽  
The One

Abstract This paper shows the realization of arguments of Latinate double object verbs and an analysis of their inherent semantic meaning in the Late Middle English and early Modern English periods, hence in the time-span when they were borrowed into English. The main aim of this paper is to show that although Latinate verbs occur in a construction with what seems to be an allative preposition, not all of them lexicalize movement in the inherent meanings. In contrast, some Latinate verbs lexicalize only a caused possession. What is more, this paper shows that the caused possession Latinate verbs select a different variant of prepositional object construction than the one selected by Latinate verbs lexicalizing movement.

scholarly journals Discrete Entailment-Based Linking and -EE Nouns in English

2007 ◽  
Vol 5 ◽  
pp. 51-79
Author(s):  
Luis González
Keyword(s):  
Semantic Analysis ◽  
Logical Structure ◽  
Direct Object ◽  
Natural Class ◽  
Object A ◽  
Role And Reference Grammar ◽  
Indirect Object ◽  
Its Analysis ◽  
Reference Grammar ◽  
Prepositional Object

Barker (1998) argues that since the referent of an -ee noun can be an indirect object, a direct object, a prepositional object, or a subject, -ee nouns cannot be described as a syntactic natural class. Portero Muñoz (2003) concurs and offers a semantic analysis based on Logical Structure (LS) in the framework of Role and Reference Grammar (RRG). This article proposes that RRG’s macroroles (Actor and Undergoer) can be derived with two entailments and without any need for LS. Its analysis improves Portero Muñoz’s, presenting additional evidence that subjects that allow -ee noun formation are Undergoers. It also explains why most -ee nouns are direct objects in spite of the fact that the suffi Xoriginated as a referent for indirect objects. Finally, it offers an explanation for nouns like amputee, pluckee, twistee, benefactee, malefactee, biographee, catapultee, razee, standee, attendee.

scholarly journals The Neural Correlates of Semantic and Grammatical Encoding During Sentence Production in a Second Language: Evidence From an fMRI Study Using Structural Priming

2022 ◽  
Vol 15 ◽  
Author(s):  
Eri Nakagawa ◽  
Takahiko Koike ◽  
Motofumi Sumiya ◽  
Koji Shimada ◽  
Kai Makita ◽  
...  
Keyword(s):  
Phonological Processing ◽  
English Learners ◽  
Inferior Frontal Gyrus ◽  
Reaction Times ◽  
Error Rates ◽  
Sentence Production ◽  
Double Object ◽  
Repetition Suppression ◽  
Prepositional Object ◽  
Linguistic Process

Japanese English learners have difficulty speaking Double Object (DO; give B A) than Prepositional Object (PO; give A to B) structures which neural underpinning is unknown. In speaking, syntactic and phonological processing follow semantic encoding, conversion of non-verbal mental representation into a structure suitable for expression. To test whether DO difficulty lies in linguistic or prelinguistic process, we conducted functional magnetic resonance imaging. Thirty participants described cartoons using DO or PO, or simply named them. Greater reaction times and error rates indicated DO difficulty. DO compared with PO showed parieto-frontal activation including left inferior frontal gyrus, reflecting linguistic process. Psychological priming in PO produced immediately after DO and vice versa compared to after control, indicated shared process between PO and DO. Cross-structural neural repetition suppression was observed in occipito-parietal regions, overlapping the linguistic system in pre-SMA. Thus DO and PO share prelinguistic process, whereas linguistic process imposes overload in DO.

scholarly journals Which Sentence Embeddings and Which Layers Encode Syntactic Structure?

2020 ◽  
Author(s):  
M. Alex Kelly ◽  
Yang Xu ◽  
Jesús Calvillo ◽  
David Reitter
Keyword(s):  
Syntactic Structure ◽  
Dimensional Space ◽  
Language Model ◽  
Empirical Support ◽  
Language Models ◽  
Double Object ◽  
Different Types ◽  
Prepositional Object ◽  
High Degree ◽  
Shed Light

Recent models of language have eliminated syntactic-semantic dividing lines. We explore the psycholinguistic implications of this development by comparing different types of sentence embeddings in their ability to encode syntactic constructions. Our study uses contrasting sentence structures known to cause syntactic priming effects, that is, the tendency in humans to re- peat sentence structures after recent exposure. We compare how syntactic alternatives are captured by sentence embed- dings produced by a neural language model (BERT) or by the composition of word embeddings (BEAGLE, HHM, GloVe). Dative double object vs. prepositional object and active vs. passive sentences are separable in the high-dimensional space of the sentence embeddings and can be classified with a high degree of accuracy. The results lend empirical support to the modern, computational, integrated accounts of semantics and syntax, and they shed light on the information stored at different layers in deep language models such as BERT.

scholarly journals From Graphematics to Phrasal, Sentential, and Textual Semantics Through Morphosyntax by Means of Corpus-Driven Grammar and Ontology: A Case Study on One Tibetan Text

2021 ◽  
Vol 72 (2) ◽  
pp. 319-329
Author(s):  
Aleksei Dobrov ◽  
Maria Smirnova
Keyword(s):  
Language Processing ◽  
Semantic Analysis ◽  
Formal Model ◽  
Semantic Annotation ◽  
Current Approach ◽  
Fine Tuning ◽  
Syntactic Analysis ◽  
Formal Grammar ◽  
Analysis Of Error

Abstract This article presents the current results of an ongoing study of the possibilities of fine-tuning automatic morphosyntactic and semantic annotation by means of improving the underlying formal grammar and ontology on the example of one Tibetan text. The ultimate purpose of work at this stage was to improve linguistic software developed for natural-language processing and understanding in order to achieve complete annotation of a specific text and such state of the formal model, in which all linguistic phenomena observed in the text would be explained. This purpose includes the following tasks: analysis of error cases in annotation of the text from the corpus; eliminating these errors in automatic annotation; development of formal grammar and updating of dictionaries. Along with the morpho-syntactic analysis, the current approach involves simultaneous semantic analysis as well. The article describes semantic annotation of the corpus, required by grammar revision and development, which was made with the use of computer ontology. The work is carried out with one of the corpus texts – a grammatical poetic treatise Sum-cu-pa (VII c.).

Discovering Data and Information Quality Research Insights Gained through Latent Semantic Analysis

2012 ◽  
Vol 3 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Roger Blake ◽  
Ganesan Shankaranarayanan
Keyword(s):  
Business Intelligence ◽  
Latent Semantic Analysis ◽  
Information Quality ◽  
Semantic Analysis ◽  
Recent Decade ◽  
Research Area ◽  
Quality Research ◽  
The Core ◽  
Data Querying ◽  
Do So

In the recent decade, the field of data and information quality (DQ) has grown into a research area that spans multiple disciplines. The motivation here is to help understand the core topics and themes that constitute this area and to determine how those topics and themes from DQ relate to business intelligence (BI). To do so, the authors present the results of a study which mines the abstracts of articles in DQ published over the last decade. Using Latent Semantic Analysis (LSA) six core themes of DQ research are identified, as well as twelve dominant topics comprising them. Five of these topics--decision support, database design and data mining, data querying and cleansing, data integration, and DQ for analytics--all relate to BI, emphasizing the importance of research that combines DQ with BI. The DQ topics from these results are profiled with BI, and used to suggest several opportunities for researchers.

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