From movement into action to manner of causation: changes in argument mapping in the into-causative

Over the last 300 years, the into-causative (he talked his father into giving him money) increased in frequency and lexical diversity. Changes of this kind are often taken as evidence of functional expansion. From a Construction Grammar (CxG) perspective, this paper argues that what appears to be a loss of restrictions on the verbal slot results from changes in argument mapping links. As the construction provides the argument roles by mapping semantics (causer, causee, result) onto syntax (subject, object, oblique), stronger mapping links increasingly facilitated the use of verbs that are semantically and syntactically atypical for the expression of causation. Data from the Corpus of Historical American English confirm three predictions of this hypothesis with respect to shifts in (i) the semantic classes of matrix verbs, (ii) their general argument structure preferences, and (iii) voice-marking. The results provide evidence for a subtle semantic change from movement into action to manner of causation. The increase in frequency and productivity are hence explained as the consequence of the syntactic form becoming a more reliable cue for causative meaning. We discuss implications for models of language change against the background of current issues in Diachronic Construction Grammar (DCxG) pertaining to constructionalization vs. constructional change.

PERAN KHUSUS VERBA “MEMASAK” DALAM BAHASA BALI: KAJIAN METABAHASA SEMANTIK ALAMI (MSA)

Observasion of Special Role of Verba”Memasak”” Bali Language (VMBB): Metalanguage Analysis of Natural Semantic analyses semantic aspect, firstly lexical realization and verb classification “memasak” in Bali langage (VMBB) mainly special role of argument semantic VMBB. Determination of the argument roles VMBB using theory of general role (Macroroles) analyses semantic role VMBB. Im general, ACTOR in VMBB acts as agent, UNDERGOER act as patient. Role analyses in this observation are done in layers to determine a semantic in an argument. The analyses of this observation use the design of qualitative observation, meanwhile the collection of data is done by observation method, interview, recording, and noting. Data analysis is done by distributional method by using replacement technique (substitution). The next method is description of special role of verb “memasak” in Bali language (VMBB). Analysis is assisted with explication technique. The presentation of result analysis of the data is done by the method of description, formal, and informal. Lexicon of verba”memasak” in Bali language (VMBB) is found 12 firstly: nyakan,mubuh, ngoreng, ngepes, ngnyahnyah, nadang, nunu, nambus, ngatim, nguskus, nguling, and nglablab.The result of observation shous that the lexion of VMBB have special role firstly as agent and patient.

Extracting Entities and Events as a Single Task Using a Transition-Based Neural Model

The task of event extraction contains subtasks including detections for entity mentions, event triggers and argument roles. Traditional methods solve them as a pipeline, which does not make use of task correlation for their mutual benefits. There have been recent efforts towards building a joint model for all tasks. However, due to technical challenges, there has not been work predicting the joint output structure as a single task. We build a first model to this end using a neural transition-based framework, incrementally predicting complex joint structures in a state-transition process. Results on standard benchmarks show the benefits of the joint model, which gives the best result in the literature.

One for All: Neural Joint Modeling of Entities and Events

The previous work for event extraction has mainly focused on the predictions for event triggers and argument roles, treating entity mentions as being provided by human annotators. This is unrealistic as entity mentions are usually predicted by some existing toolkits whose errors might be propagated to the event trigger and argument role recognition. Few of the recent work has addressed this problem by jointly predicting entity mentions, event triggers and arguments. However, such work is limited to using discrete engineering features to represent contextual information for the individual tasks and their interactions. In this work, we propose a novel model to jointly perform predictions for entity mentions, event triggers and arguments based on the shared hidden representations from deep learning. The experiments demonstrate the benefits of the proposed method, leading to the state-of-the-art performance for event extraction.

Wait a second! Delayed impact of argument roles on on-line verb prediction

Comprehenders can use rich contextual information to anticipate upcoming input on the fly, but recent findings suggest that salient information about argument roles may not impact verb prediction. We took advantage of the word order properties of Mandarin Chinese to examine the time course with which argument role information impacts verb prediction. We isolated the contribution of argument role information by manipulating the order of pre-verbal noun phrase arguments while holding lexical information constant, and we examined its effects on accessing the verb in long-term semantic memory by measuring the amplitude of the N400 component. Experiment 1 showed when the verb appeared immediately after its arguments, even strongly constraining argument role information failed to modulate the N400 response to the verb. An N400 effect emerged in Experiment 2 when the verb appeared at a greater delay. Experiment 3 corroborated the contrast between the first two experiments through a within-participants manipulation of the time interval between the arguments and the verb, by varying the position of an adverbial phrase. These results suggest time is a key factor governing how diverse contextual information contributes to predictions. Here argument role information is shown to impact verb prediction, but its effect is not immediate.

On the perfect tense-aspect in K'ichee'an Mayan: An LFG approach

Previous accounts of the perfect tense-aspect in the K'ichee'an languages have concluded that the category or part-of-speech of the perfect is a verb, or less often, a participle. We believe otherwise. Empirical support is presented for the hypothesis that the perfect is expressed using either a deverbal participial adjective or a deverbal possessed nominal in the form of a detransitivized non-verbal predicate. We show that the perfect always consists of a one-place intransitive but that it, nonetheless, retains the capacity to express two argument roles. Further, we argue that the perfect is, in fact, a perfect. We present the various semantic types of perfect, including the perfect of result and the experiential perfect, and also show the temporal restrictions that constrain the perfect. The analyses are implemented using the syntactic architecture of LFG.

Idiosyncrasies and generalizations: Argument structure, semantic roles and the valency realization principle

This article argues in favour of dealing with valency phenomena and collocations in terms of constructions. An attempt is made to combine Goldberg’s model of argument structure constructions with item-specific valency constructions. It is argued that it may be appropriate to distinguish not only between verb-specific participant roles and argument roles, but to introduce a further level of clausal roles to account for AGENTIVITY and AFFECTEDNESS typically associated with subjects and traditional direct objects. Finally, the issue of to what extent the syntactic behaviour of verbs can be predicted from their meaning is taken up and it is shown that Goldberg’s Semantic Coherence Principle and Correspondence Principle have to be supplemented by a Valency Realisation Principle.

Argument kinds and argument roles in the Ontario provincial election, 2011

This paper is a report of a pilot study of how candidates argue when they are running for political office. The election studied was the provincial election in Ontario, Canada, in the fall of 2011. Having collected about 250 arguments given during the election from newspaper media, we sought answers to the following questions, among others: (i) which argumentation schemes have the greatest currency in political elections? (ii) Is a list of the best known argumentation schemes sufficient to classify the arguments given in elections? (iii) What schemes should be added to the familiar list to make it more adequate for studying elections? (iv) Is it useful to classify arguments as being used for positive, policy-critical, person-critical and defensive purposes? (v) Can political parties be usefully characterized by noting their preferred kinds of arguments and their most frequent uses of arguments? (vi) What lessons can be learned from this study to better design future studies of the same kind?

Transitivity in Abui

This paper explores transitivity-related features in Abui, a language with fluid semantic alignment (after Donohue and Wichmann 2008). Many known semantically aligned languages distinguish between two argument roles: actor and undergoer (e.g. Merlan 1985; Durie 1987; Mithun 1991, Donohue and Wichmann 2008 and papers therein). Abui system is unusual; it offers seven coding options for both single-argument and two-argument clauses. A rich set of semantic features (specificity, animacy, individuation, instigation, control, volition, affectedness, change, and change of state) drive the differential realisation of arguments. These features are known to be relevant to transitivity, differential argument marking, and split intransitivity. The paper presents a detailed analysis of these features, and explores their ranking, correlations, and clustering. Based on the Abui system, the paper characterises transitivity as a scalar and constructional phenomenon (refining Hopper and Thompson 1980; Rozwadowska 1988; and Næss 2007) applying only to a subset of two-argument clauses because there is no clear default two-argument construction that contains both actor and undergoer arguments.