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# Claire Gardent

3 paper cards in Mova's library · 2016–2021

Claire Gardent wrote 3 of the papers Mova reads, in 2016–2021, most of them on [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/); often with [Anastasia Shimorina](https://md.mova.elamur.ai/free/en/docs/papers/authors/anastasia-shimorina/), [Shashi Narayan](https://md.mova.elamur.ai/free/en/docs/papers/authors/shashi-narayan/), Laura Perez-Beltrachini.

[OpenAlex](https://openalex.org/A5087459652) · [ORCID](https://orcid.org/0000-0002-3805-6662) · [**h-index 28**](https://openalex.org/authors/A5087459652) · [3991 citations](https://openalex.org/authors/A5087459652) · [405 works](https://openalex.org/works?filter=author.id:A5087459652) — openalex, 2026-10-18

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=Claire+Gardent) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Claire+Gardent) · [dblp](https://dblp.org/search?q=Claire+Gardent) · [ACL Anthology](https://aclanthology.org/search/?q=Claire+Gardent) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Claire+Gardent)

Topics: [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/) 3

## Papers

1. **[An Error Analysis Framework for Shallow Surface Realization](https://md.mova.elamur.ai/free/en/docs/papers/shimorina-2021-error-analysis-framework-shallow-surface/)** *(2021)* Scores such as BLEU say how good a system is but not which input features make it fail. The paper offers an error analysis for shallow surface realisation with two parts. The first part correlates syntactic complexity metrics of the input trees (tree shape, projectivity, entropy of dependency relations) with the…
2. **[The WebNLG Challenge: Generating Text from RDF Data](https://md.mova.elamur.ai/free/en/docs/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.
3. **[Unsupervised Sentence Simplification Using Deep Semantics](https://md.mova.elamur.ai/free/en/docs/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 (4)

- [Anastasia Shimorina](https://md.mova.elamur.ai/free/en/docs/papers/authors/anastasia-shimorina/) ×2
- [Shashi Narayan](https://md.mova.elamur.ai/free/en/docs/papers/authors/shashi-narayan/) ×2
- Laura Perez-Beltrachini
- Yannick Parmentier
- [← previous Claire Bonial](https://md.mova.elamur.ai/free/en/docs/papers/authors/claire-bonial/)
- [next → Colin Cherry](https://md.mova.elamur.ai/free/en/docs/papers/authors/colin-cherry/)
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