The state of the art in semantic representation
O Abend, A Rappoport - Proceedings of the 55th Annual Meeting …, 2017 - aclanthology.org
Semantic representation is receiving growing attention in NLP in the past few years, and
many proposals for semantic schemes (eg, AMR, UCCA, GMB, UDS) have been put forth …
many proposals for semantic schemes (eg, AMR, UCCA, GMB, UDS) have been put forth …
Evaluating factuality in generation with dependency-level entailment
Despite significant progress in text generation models, a serious limitation is their tendency
to produce text that is factually inconsistent with information in the input. Recent work has …
to produce text that is factually inconsistent with information in the input. Recent work has …
A survey on open information extraction
We provide a detailed overview of the various approaches that were proposed to date to
solve the task of Open Information Extraction. We present the major challenges that such …
solve the task of Open Information Extraction. We present the major challenges that such …
MultiOIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT
In this paper, we propose Multi $^ 2$ OIE, which performs open information extraction (open
IE) by combining BERT with multi-head attention. Our model is a sequence-labeling system …
IE) by combining BERT with multi-head attention. Our model is a sequence-labeling system …
Falsesum: Generating document-level NLI examples for recognizing factual inconsistency in summarization
Neural abstractive summarization models are prone to generate summaries which are
factually inconsistent with their source documents. Previous work has introduced the task of …
factually inconsistent with their source documents. Previous work has introduced the task of …
XL-AMR: Enabling cross-lingual AMR parsing with transfer learning techniques
Meaning Representation (AMR) is a popular formalism of natural language that represents
the meaning of a sentence as a semantic graph. It is agnostic about how to derive meanings …
the meaning of a sentence as a semantic graph. It is agnostic about how to derive meanings …
Broad-coverage semantic parsing as transduction
We unify different broad-coverage semantic parsing tasks under a transduction paradigm,
and propose an attention-based neural framework that incrementally builds a meaning …
and propose an attention-based neural framework that incrementally builds a meaning …
Ordinal common-sense inference
Humans have the capacity to draw common-sense inferences from natural language:
various things that are likely but not certain to hold based on established discourse, and are …
various things that are likely but not certain to hold based on established discourse, and are …
Alignment-augmented consistent translation for multilingual open information extraction
Abstract Progress with supervised Open Information Extraction (OpenIE) has been primarily
limited to English due to the scarcity of training data in other languages. In this paper, we …
limited to English due to the scarcity of training data in other languages. In this paper, we …
Universal semantic parsing
Universal Dependencies (UD) offer a uniform cross-lingual syntactic representation, with the
aim of advancing multilingual applications. Recent work shows that semantic parsing can be …
aim of advancing multilingual applications. Recent work shows that semantic parsing can be …