[PDF] Top 20 World Knowledge for Abstract Meaning Representation Parsing

... integrate world knowledge into the CAMR parser (Wang et ...integrate world knowledge into this parser, we change the feature set generated by each node in the current context ...the ... See full document

... cross-framework meaning representation initia- tive are to advance our understanding of degrees of complementarity among the various ...course Representation Structures of Basile et ...include ... See full document

... the representation (ii) there are a variety of fairly ro- bust AMR parsers we can employ for this work, enabling us to forego manual annotation of sub- stantial portions of our data and facilitating ef- ficient ... See full document

... a representation of the relations among entities in ...the Abstract Mean- ing Representation (AMR) can better capture and represent the contexts of entity mentions for EL than previous ...AMR ... See full document

... On top of the local features used in the base- line MaxEnt classifier, we exploit knowledge from AMR parse graphs to add AMR features into the MaxEnt classifier. The effects of these features have been explored ... See full document

... AMR parsing results seems relatively worse on this pre-processed data since, for example, many low-occurrence words in the data were already re- placed with ... See full document

... ples of its expressions (Lee, 1996). Most of the approaches directly learn a grammar from the ex- pressions but there also have been approaches that first start with a simple grammar and then trans- form it using ... See full document

... Abstract Meaning Representation (AMR) parsing aims at abstracting away from the syn- tactic realization of a sentence, and denoting only its meaning in a canonical ...AMR parsing ... See full document

... semantic representation (see Sec- tion 7 for related ...accurate parsing of natural language to a structured representation, as well as ease of conversion of this broad coverage representation ... See full document

... Our general roleset is very similar (in definition, albeit dis- tinct in labeling) to that of Bakhshandeh and Allen (2015), who aim to predict the predicate-argument structure of com- parison sentences to support ... See full document

... The table highlights some of our results. Firstly, we note that, in cases where we obtain a large number of extra sentences using distant supervi- sion (highlighted in the column “DS Sents”), we see a considerable gain ... See full document

... We showed that semantic relations among sentence items can improve the current summarization eval- uation metrics. The approach is very sensitive to the quality of the AMR parser. It is expected to improve when AMR ... See full document

... To our knowledge, our system is the first for gen- erating English from AMR. The approach is a sta- tistical natural language generation (NLG) system, trained discriminatively using sentences in the AMR bank ... See full document

... The news texts were extracted from RSS 1 from Folha de S˜ao Paulo news agency 2 , one of the mainstream agencies in Brazil. The selected news came from different sections/domains: “daily news”, “world news”, ... See full document

... Although AKR, AMR, DRT and DepLambda are the closest to our representations, there are a couple of other approaches that can be viewed as a step towards producing semantic representations for semantic processing. ... See full document

... Several parsers for AMR have been recently de- veloped (Flanigan et al., 2014; Wang et al., 2015a; Peng et al., 2015; Pust et al., 2015; Goodman et al., 2016; Rao et al., 2015; Vanderwende et al., 2015; Artzi et al., ... See full document

... In this paper we present the first set of manually aligned English/AMR pairs, as well as the first published system for learning the alignments be- tween English sentences and AMR graphs that provides a strong baseline ... See full document

... To train the parser, spans of words must be la- beled with the concept fragments they evoke. Al- though AMR Bank does not label concepts with the words that evoke them, it is possible to build an automatic aligner (§5). ... See full document

... dependency parsing (Goldberg and Nivre, 2013), and feature selection (He et ...AMR parsing, which has a more complex out- put space than those considered ... See full document

... The first work that addressed AMR parsing was that of Flanigan et al. (2014). In that work, mul- tiple discriminatively trained models are used to identify individual concept instances and then a minimum spanning ... See full document