Towards Universal Semantic Representation

Zhu, Huaiyu; Li, Yunyao; Chiticariu, Laura

doi:10.18653/v1/w19-3320

Cited by 14 publications

(8 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cross-lingual approaches to AMR parsing explore transfer learning techniques to generate parallel AMR annotations in multiple languages, and suggest that AMR can serve as a cross-lingual semantic representation capable of overcoming linguistic differences (Damonte and Cohen, 2018;Zhu et al, 2019;Blloshmi et al, 2020).…”

Section: Use Of Amr In Many Languages Andmentioning

confidence: 99%

Classifying Divergences in Cross-lingual AMR Pairs

Wein¹,

Schneider²

2021

Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop

View full text Add to dashboard Cite

Translation divergences are varied and widespread, challenging approaches that rely on parallel text. To annotate translation divergences, we propose a schema grounded in the Abstract Meaning Representation (AMR), a sentence-level semantic framework instantiated for a number of languages. By comparing parallel AMR graphs, we can identify specific points of divergence. Each divergence is labeled with both a type and a cause. We release a small corpus of annotated English-Spanish data, and analyze the annotations in our corpus.

show abstract

Section: Use Of Amr In Many Languages Andmentioning

confidence: 99%

Classifying Divergences in Cross-lingual AMR Pairs

Wein¹,

Schneider²

2021

Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop

View full text Add to dashboard Cite

show abstract

“…7 SystemT also provides additional information, such as tense and voice; please refer to (Zhu et al, 2019) for details.…”

Section: Model Developmentmentioning

confidence: 99%

Development of an Enterprise-Grade Contract Understanding System

Agarwal¹,

Chiticariu²,

Raman³

et al. 2021

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

Self Cite

View full text Add to dashboard Cite

Contracts are arguably the most important type of business documents. Despite their significance in business, legal contract review largely remains an arduous, expensive and manual process. In this paper, we describe the Transparent and Expert Contract Understanding System (TECUS): a commercial system designed and deployed for contract understanding and used by a wide range of enterprise users for the past few years. We reflect on the challenges and design decisions when building TECUS. We also summarize the data science life cycle of TECUS and share lessons learned.

show abstract

“…Kuhlmann and Oepen (2016) follow up on the SemEval paper and describe graph properties of the three frameworks from the SemEval task, plus CCG Dependencies and Abstract Meaning Representation. Zhu, Li, and Chiticariu (2019) take two approaches, namely, the semantic role labeling approach of the PropBank project and Abstract Meaning Representation, as a point of departure to propose and discuss which issues are to be covered by the universal semantic representation (with the focus on temporal features and modality).…”

Section: Existing Surveysmentioning

confidence: 99%

Sentence Meaning Representations Across Languages: What Can We Learn from Existing Frameworks?

Žabokrtský

Zeman

Ševčíková

2020

Computational Linguistics

View full text Add to dashboard Cite

This article gives an overview of how sentence meaning is represented in eleven deep-syntactic frameworks, ranging from those based on linguistic theories elaborated for decades to rather lightweight NLP-motivated approaches. We outline most important characteristics of each framework and then discuss how particular language phenomena are treated across those frameworks, while trying to shed light on commonalities as well as differences.

show abstract

Towards Universal Semantic Representation

Cited by 14 publications

References 4 publications

Classifying Divergences in Cross-lingual AMR Pairs

Classifying Divergences in Cross-lingual AMR Pairs

Development of an Enterprise-Grade Contract Understanding System

Sentence Meaning Representations Across Languages: What Can We Learn from Existing Frameworks?

Contact Info

Product

Resources

About