--- title: "Shashi Narayan — papers and cards" description: "Shashi Narayan: 2 paper cards in the Research library (2016–2017), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/shashi-narayan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/shashi-narayan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Shashi Narayan # Shashi Narayan 2 paper cards in the Research library · 2016–2017 Shashi Narayan wrote 2 of the papers Mova reads, in 2016–2017, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Claire Gardent](https://md.research.elamur.ai/free/en/authors/claire-gardent/), [Anastasia Shimorina](https://md.research.elamur.ai/free/en/authors/anastasia-shimorina/), Laura Perez-Beltrachini. [OpenAlex](https://openalex.org/A5081801388) · [**h-index 27**](https://openalex.org/authors/A5081801388) · [6112 citations](https://openalex.org/authors/A5081801388) · [92 works](https://openalex.org/works?filter=author.id:A5081801388) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Shashi+Narayan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Shashi+Narayan) · [dblp](https://dblp.org/search?q=Shashi+Narayan) · [ACL Anthology](https://aclanthology.org/search/?q=Shashi+Narayan) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Shashi+Narayan) Topics: [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 2 ## Papers 1. **[The WebNLG Challenge: Generating Text from RDF Data](https://md.research.elamur.ai/free/en/papers/gardent-2017-webnlg-challenge-generating-text-rdf/)** *(2017)* The WebNLG challenge maps sets of RDF triples taken from DBpedia to text, and is built to test microplanning: referring expressions, aggregation, lexicalisation, surface realisation and sentence segmentation chosen together. 2. **[Unsupervised Sentence Simplification Using Deep Semantics](https://md.research.elamur.ai/free/en/papers/narayan-2016-unsupervised-sentence-simplification-deep-semantics/)** *(2016)* The system simplifies sentences with neither hand-written rules nor an aligned training corpus. It parses each sentence into a discourse representation structure (DRS), a deep semantic graph whose nodes are events and entities, and applies substitution, reordering, splitting and deletion on that graph, not on words… ## Co-authors (3) - [Claire Gardent](https://md.research.elamur.ai/free/en/authors/claire-gardent/) ×2 - [Anastasia Shimorina](https://md.research.elamur.ai/free/en/authors/anastasia-shimorina/) - Laura Perez-Beltrachini ## More papers in the library (2) Pages of the Research library: our summary, the ideas, references and who cites each. - [Leveraging Pre-trained Checkpoints for Sequence Generation Tasks](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/) — Sascha Rothe, Shashi Narayan, Aliaksei Severyn · 2019 - [Creating Training Corpora for NLG Micro-Planners](https://md.research.elamur.ai/free/en/papers/gardent-2017-creating-training-corpora-nlg-micro/) — Claire Gardent, Anastasia Shimorina, Shashi Narayan, et al. · 2017