Semantic knowledge may be organized in terms of similarity relations based on shared features and/or complementary relations based on co-occurrence in events. Thus, relationships between manipulable objects such as tools may be defined by their functional properties (what the objects are used for) or thematic properties (e.g., what the objects are used with or on). A recent study from our labor...

Different semantic interpretation tasks such as text entailment and question answering require the classification of semantic relations between terms or entities within text. However, in most cases it is not possible to assign a direct semantic relation between entities/terms. This paper proposes an approach for composite semantic relation classification, extending the traditional semantic rela...

Most set expansion algorithms assume to acquire new instances of different semantic categories independently even when we have seed instances of multiple semantic categories. However, in the setting of set expansion with multiple semantic categories, we might leverage other types of prior knowledge about semantic categories. In this paper, we present a method of set expansion when ontological i...

Ontologies and possibilities of using and enhancing them is a currently widespread research area.Widely unused are relations between concepts defined in ontologies in the context of knowledge representation. In this paper, the potential of using a semantic network to support the automatic generation of semantic structures is analysed. Semantic representations to unstructured natural language do...

Inductive and deductive inferences in a Crowdsourced Lexical-Semantic Network In Computational Linguistics, validated lexical-semantic networks are crucial resources. Regardless the construction strategies used, automatically inferring new relations from already existing ones may improve coverage and global quality of the resource. In this context, an inference engine aims at producing new conc...

In this project, we have studied Chinese noun-noun compounds (NNCs) and have found that N1 and N2 are linked either by semantic roles assigned by events (complex relations) or by static relations (simple relations), including meronymy, conjunction, and the host-attribute-value relation. Using data from the FrameNet and E-HowNet, we have found that, for NNCs of either type, the major semantic re...

We propose a method for semantic structure analysis of noun phrases using Abstract Meaning Representation (AMR). AMR is a graph representation for the meaning of a sentence, in which noun phrases (NPs) are manually annotated with internal structure and semantic relations. We extract NPs from the AMR corpus and construct a data set of NP semantic structures. We also propose a transition-based al...

We induce semantic association networks from translation relations in parallel corpora. The resulting semantic spaces are encoded in a single reference language, which ensures cross-language comparability. As our main contribution, we cluster the obtained (crosslingually comparable) lexical semantic spaces. We find that, in our sample of languages, lexical semantic spaces largely coincide with ...

We report on a pilot study of techniques for organizing terms derived from relevant corpora into semantic clusters. We combine rule-based techniques and an unsupervised statistical method to semantically cluster terms extracted from medical reports. The rule-based approach identifies lexicosyntactic patterns suggestive of parent-child relations and coordination structures suggestive of sibling-...

Semantic relations play an important role in linguistic knowledge representation. Although their role is relevant in the context of written text, there is no approach or dataset that makes use of contextuality of classic semantic relations beyond the boundary of one sentence. We present the SemRelData dataset that contains annotations of semantic relations between nominals in the context of one...