Semantic Inheritance Research Articles

From work one’s ass off to bite one’s face off: Understanding the degree of idiomaticity through syntactic and semantic inheritance in a network of (originally) resultative constructions

From work one’s ass off to bite one’s face off: Understanding the degree of idiomaticity through syntactic and semantic inheritance in a network of (originally) resultative constructions

Semantic Inheritance in the Lexical Paradigms of Old English Strong Verbs

This work delves into the semantics of Old English lexical paradigms based on strong verbs. Its aim is to describe the patterns of semantic inheritance that hold in these paradigms, which present morphologically related words sharing the form and meaning of the base of derivation. The analysis carried out permits to circumscribe semantic derivation in these Old English lexical paradigms into the lexical entailment relations of troponymy, -troponymy, backward presupposition and cause, and the semantic relations of synonymy and opposition. The data of research has been retrieved from the lexical database Nerthus (Martín Arista et. al 2016). On the theoretical side, this examination follows the English lexical database WordNet (Princeton, 2010). This research unfolds a systematic methodology that is thoroughly described and illustrated by means of the paradigm (ge)berstan. It has not only been possible to circumscribe semantic derivation into the six semantic relations mentioned, but also to determine their frequency of occurrence in the paradigms under analysis, which indicates that synonymy and troponymy are the most recurrent semantic relations.

Hierarchical Sliding Inference Generator for Question-driven Abstractive Answer Summarization

Text summarization on non-factoid question answering (NQA) aims at identifying the core information of redundant answer guidance using questions, which can dramatically improve answer readability and comprehensibility. Most existing approaches focus on extracting query-related sentences to construct a summary, where the logical connection of natural language and the hierarchical interpretable semantic association are often neglected, thus degrading performance. To address these issues, we propose a novel question-driven abstractive answer summarization model, called the H ierarchical S liding I nference G enerator (HSIG), to form inferable and interpretable summaries by explicitly introducing hierarchical information reasoning between questions and corresponding answers. Specifically, we first apply an elaborately designed hierarchical sliding fusion inference model to determine the most relevant question sentence-level representation that provides a deeper interpretable basis for sentence selection in summarization, which further increases computational performance on the premise of following the semantic inheritance structure. Additionally, to improve summary fluency, we construct a double-driven selective generator to integrate various semantic information from two mutual question-and-answer perspectives. Experimental results illustrate that compared with state-of-the-art baselines, our model achieves remarkable improvement on two benchmark datasets and specifically improves the 2.46 ROUGE-1 points on PubMedQA, which demonstrates the superiority of our model on abstractive summarization with hierarchical sequential reasoning.

Compostos com síndrome e complexo no português brasileiro: uma abordagem construcional

Neste trabalho, serão estudados os compostos instanciados pelos esquemas [Síndrome [X]]N e [Complexo [SP]]N, com base nos pressupostos teóricos da Morfologia Construcional (BOOIJ, 2010; GONÇALVES, 2016). Os dados foram coletados em publicações de sites brasileiros, no século XXI. Alguns exemplos encontrados são síndrome de Peterpan, complexo de Wendy, complexo de vira-lata, complexo de Cinderela e síndrome de Dona Florinda. Este estudo ainda visa contribuir com as discussões acerca da herança semântica em relação aos compostos. Para isso, foi revisitada a pouca literatura sobre o assunto, o que inclui Corbin (1990), Booij (2017) e Soledade (2018a), tendo esses autores atentado mais contundentemente para aspectos da derivação sufixal.

GO2PUB: Querying PubMed with semantic expansion of gene ontology terms

BackgroundWith the development of high throughput methods of gene analyses, there is a growing need for mining tools to retrieve relevant articles in PubMed. As PubMed grows, literature searches become more complex and time-consuming. Automated search tools with good precision and recall are necessary. We developed GO2PUB to automatically enrich PubMed queries with gene names, symbols and synonyms annotated by a GO term of interest or one of its descendants.ResultsGO2PUB enriches PubMed queries based on selected GO terms and keywords. It processes the result and displays the PMID, title, authors, abstract and bibliographic references of the articles. Gene names, symbols and synonyms that have been generated as extra keywords from the GO terms are also highlighted. GO2PUB is based on a semantic expansion of PubMed queries using the semantic inheritance between terms through the GO graph. Two experts manually assessed the relevance of GO2PUB, GoPubMed and PubMed on three queries about lipid metabolism. Experts’ agreement was high (kappa = 0.88). GO2PUB returned 69% of the relevant articles, GoPubMed: 40% and PubMed: 29%. GO2PUB and GoPubMed have 17% of their results in common, corresponding to 24% of the total number of relevant results. 70% of the articles returned by more than one tool were relevant. 36% of the relevant articles were returned only by GO2PUB, 17% only by GoPubMed and 14% only by PubMed. For determining whether these results can be generalized, we generated twenty queries based on random GO terms with a granularity similar to those of the first three queries and compared the proportions of GO2PUB and GoPubMed results. These were respectively of 77% and 40% for the first queries, and of 70% and 38% for the random queries. The two experts also assessed the relevance of seven of the twenty queries (the three related to lipid metabolism and four related to other domains). Expert agreement was high (0.93 and 0.8). GO2PUB and GoPubMed performances were similar to those of the first queries.ConclusionsWe demonstrated that the use of genes annotated by either GO terms of interest or a descendant of these GO terms yields some relevant articles ignored by other tools. The comparison of GO2PUB, based on semantic expansion, with GoPubMed, based on text mining techniques, showed that both tools are complementary. The analysis of the randomly-generated queries suggests that the results obtained about lipid metabolism can be generalized to other biological processes. GO2PUB is available at http://go2pub.genouest.org.

No bootstrapping without semantic inheritance

AbstractAnderson's massive redeployment hypothesis (MRH) takes the grounding of meaning in sensorimotor behaviour to be a side effect of neural reuse. I suggest this grounding may play a much more fundamental role in accounting for the bootstrapping of higher-level cognition from sensorimotor behaviour. Thus, the question of when neural reuse delivers semantic inheritance is a pressing one for MRH.

Semantic inheritance in unifying theories of programming

Abstract This paper introduces a number of new techniques that support systematic manipulation of predicates, operators, healthiness conditions, laws and fixpoints of recursive programs. Necessary restrictions are imposed on the definition of each model so that the inheritance relation can be established by checking a few conditions on the healthiness conditions and the commands. In particular, we intend to identify the conditions that simplify the closure proof of the program operators and enable laws and fixpoints of a model to be inherited by its submodel without re-proof. A recursive program may correspond to different recursive functions in a model and its submodels, because the primitives such as abort and assignment statements are normally represented as different predicates in different models (although the original definition of each operator is unchanged). This paper studies meta-theory in this more general setting. A fixpoint theorem is discovered and applied to clarify the relationship between the partially correct relational model and the totally correct sequential model in UTP. It is shown that, although assignment statements are modified by the new healthiness conditions in the latter model, most laws (including many that are re-proved in UTP) and fixpoints can be inherited directly without re-proof, if the first argument of every sequential composition in each command tree corresponds to a terminating computation. This result also singles out a small number of laws and fixpoints that may no longer hold in the totally correct model.

Life, information, entropy, and time: Vehicles for semantic inheritance

Attempts to understand how information content can be included in an accounting of the energy flux of the biosphere have led to the conclusion that, in information transmission, one component, the semantic content, or "the meaning of the message," adds no thermodynamic burden over and above costs arising from coding, transmission and translation. In biology, semantic content has two major roles. For all life forms, the message of the genotype encoded in DNA specifies the phenotype, and hence the organism that is tested against the real world through the mechanisms of Darwinian evolution. For human beings, communication through language and similar abstractions provides an additional supra-phenotypic vehicle for semantic inheritance, which supports the cultural heritages around which civilizations revolve. The following three postulates provide the basis for discussion of a number of themes that demonstrate some important consequences. (i) Information transmission through either pathway has thermodynamic components associated with data storage and transmission. (ii) The semantic content adds no additional thermodynamic cost. (iii) For all semantic exchange, meaning is accessible only through translation and interpretation, and has a value only in context. (1) For both pathways of semantic inheritance, translational and copying machineries are imperfect. As a consequence both pathways are subject to mutation and to evolutionary pressure by selection. Recognition of semantic content as a common component allows an understanding of the relationship between genes and memes, and a reformulation of Universal Darwinism. (2) The emergent properties of life are dependent on a processing of semantic content. The translational steps allow amplification in complexity through combinatorial possibilities in space and time. Amplification depends on the increased potential for complexity opened by 3D interaction specificity of proteins, and on the selection of useful variants by evolution. The initial interpretational steps include protein synthesis, molecular recognition, and catalytic potential that facilitate structural and functional roles. Combinatorial possibilities are extended through interactions of increasing complexity in the temporal dimension. (3) All living things show a behavior that indicates awareness of time, or chronognosis. The ∼4 billion years of biological evolution have given rise to forms with increasing sophistication in sensory adaptation. This has been linked to the development of an increasing chronognostic range, and an associated increase in combinatorial complexity. (4) Development of a modern human phenotype and the ability to communicate through language, led to the development of archival storage, and invention of the basic skills, institutions and mechanisms that allowed the evolution of modern civilizations. Combinatorial amplification at the supra-phenotypical level arose from the invention of syntax, grammar, numbers, and the subsequent developments of abstraction in writing, algorithms, etc. The translational machineries of the human mind, the "mutation" of ideas therein, and the "conversations" of our social intercourse, have allowed a limited set of symbolic descriptors to evolve into an exponentially expanding semantic heritage. (5) The three postulates above open interesting epistemological questions. An understanding of topics such dualism, the élan vital, the status of hypothesis in science, memetics, the nature of consciousness, the role of semantic processing in the survival of societies, and Popper's three worlds, require recognition of an insubstantial component. By recognizing a necessary linkage between semantic content and a physical machinery, we can bring these perennial problems into the framework of a realistic philosophy. It is suggested, following Popper, that the ∼4 billion years of evolution of the biosphere represents an exploration of the nature of reality at the physicochemical level, which, together with the conscious extension of this exploration through science and culture, provides a firm epistemological underpinning for such a philosophy.

Temporal logic issues in music knowledge representation

This paper shows possible applications to music of some results deriving from Temporal Reasoning (TR), a particular subfield of Artificial Intelligence (AI). In particular, TR can be usefully applied in music theory, musicology, composition, and in any activity involving reasoning on music knowledge. The basic assumption is that a general music theory has to cope deeply with formal theories of time. In the paper are briefly introduced and discussed the most relevant formalisms on TR, to investigate their possible implications in the music domain. Successively, the paper shows the formalism for TR embedded in an approach we have recently developed, consisting of a hybrid model for music knowledge representation based on SI-Nets (Semantic Inheritance Networks).

Automating Planning Environments: Knowledge Integration and Model Scripting

Abstract:Progress has been limited in understanding the nature of Information Systems (is) planning and accomplishing its goals. Two problems which contribute fundamentally are the dynamism of is and the difficulty of integrating multiple perspectives on IS planning. Automated environments which support the is planning process must address these two issues, dynamism and integration. In this paper, three perspectives on the is planning process are reviewed. Knowledge-based techniques using Semantic Inheritance Nets are described as useful for view integration and for providing a flexible, dynamic, automated model of the is planning environment which is accessible to is tools. The use of scripting in IS planning models is examined as a way to address the issue of is dynamism. Implementation of these techniques is described in plexplan, a knowledge-based environment for is planning. Application of knowledge integration and model scripting in an instance of plexplan use is described.