Семантикалық көрініс

Tense, temporal adverbs, and temporal connectives provide information about when events described in English sentences occur. To extract this temporal information from a sentence, it must be parsed into a …...

AbstractThis presentation outlines the implementation of a machine translation system for avalanche warning bulletins in natural language, using a unification-based formalism developed at ISSCO, which will be introduced at the …...

This paper will focus on the semantic representa- tion of verbs in computer systems and its impact on lexical selection problems in machine transla- tion (MT). Two groups of English …...

This paper aims to show that semantic representation of verbs may require the inclusion of constructional inferences in addition to lexical specifications. By examining the transitive pattern of the Mandarin …...

With the rapid growth of real application domains for NLP systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build specific …...

This paper describes how to perform syntactic parsing and semantic analysis using the contextual information as a language understanding component in a dialog system. Although syntactic parsing and semantic analysis …...

AbstractThe study which is reported here aims at investigating the extent to which the conceptual and representational tools provided by a lexical model designed for the semantic representation of general …...

In this paper, we report experiments that explore learning of syntactic and seman- tic representations. First, we extend a state-of-the-art statistical parser to pro- duce a richly annotated tree that …...

AbstractIn Natural Language Generation (NLG), template-based surface realisation is an effective solution to the problem of producing surface strings from a given semantic representation, but many applications may not be …...

AbstractProcedural knowledge is the knowledge required to perform certain tasks, and forms an important part of expertise. A major source of procedural knowledge is natural language instructions. While these readable …...

A popular tradition of studying semantic rep- resentation has been driven by the assump- tion that word meaning can be learned from the linguistic environment, despite ample ev- idence suggesting …...

Robustness and portability of spoken language understanding systems among languages and domains : the PORTMEDIA project The ANR PORTMEDIA projet aimed at complementing the MEDIA corpus so as to foster …...

AbstractThis paper presents a method to create WordNet-like lexical resources for different languages. Instead of directly translating glosses from one language to another, we perform first semantic parsing of WordNet …...

We propose an unsupervised approach to constructing templates from a large collec- tion of semantic category names, and use the templates as the semantic representa- tion of categories. The main …...

A common approach to unsupervised relation extraction builds clusters of patterns express- ing the same relation. In order to obtain clus- ters of relational patterns of good quality, we have …...

One major deficiency of most semantic repre- sentation techniques is that they usually model a word type as a single point in the semantic space, hence conflating all the meanings …...

Question answering forums are rapidly grow- ing in size with no effective automated abil- ity to refer to and reuse answers already avail- able for previous posted questions. In this …...

AbstractIn this paper, we introduce WoRel, a model that jointly learns word embeddings and a semantic representation of word relations. The model learns from plain text sentences and their dependency …...

AbstractSemantic representation is receiving growing attention in NLP in the past few years, and many proposals for semantic schemes (e.g., AMR, UCCA, GMB, UDS) have been put forth. Yet, little …...

AbstractFormulaic expressions (FEs) used in scholarly papers, such as ‘there has been little discussion about’, are helpful for non-native English speakers. However, it is time-consuming for users to manually search …...

AbstractCommonsenseQA is a task in which a correct answer is predicted through commonsense reasoning with pre-defined knowledge. Most previous works have aimed to improve the performance with distributed representation without …...

AbstractOne challenge in Natural Language Processing (NLP) area is to learn semantic representation in different contexts. Recent works on pre-trained language model have received great attentions and have been proven …...

AbstractRecent works have shown that supervised models often exploit data artifacts to achieve good test scores while their performance severely degrades on samples outside their training distribution. Contrast sets (Gardneret …...

AbstractExternal syntactic and semantic information has been largely ignored by existing neural coreference resolution models. In this paper, we present a heterogeneous graph-based model to incorporate syntactic and semantic structures …...

AbstractHow does the input segmentation of pretrained language models (PLMs) affect their interpretations of complex words? We present the first study investigating this question, taking BERT as the example PLM …...

AbstractRecently, pre-trained transformer-based models have achieved great success in the task of definition generation (DG). However, previous encoder-decoder models lack effective representation learning to contain full semantic components of the …...