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# Emma Manning

3 paper cards in Mova's library · 2019–2021

Emma Manning wrote 3 of the papers Mova reads, in 2019–2021, most of them on [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/); often with [Nathan Schneider](https://md.mova.elamur.ai/free/en/docs/papers/authors/nathan-schneider/), [Shira Wein](https://md.mova.elamur.ai/free/en/docs/papers/authors/shira-wein/).

[OpenAlex](https://openalex.org/A5006919541) · [**h-index 3**](https://openalex.org/authors/A5006919541) · [45 citations](https://openalex.org/authors/A5006919541) · [12 works](https://openalex.org/works?filter=author.id:A5006919541) — 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=Emma+Manning) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Emma+Manning) · [dblp](https://dblp.org/search?q=Emma+Manning) · [ACL Anthology](https://aclanthology.org/search/?q=Emma+Manning) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Emma+Manning)

Topics: [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/) 1

## Papers

1. **[Referenceless Parsing-Based Evaluation of AMR-to-English Generation](https://md.mova.elamur.ai/free/en/docs/papers/manning-2021-referenceless-parsing-based-evaluation-amr/)** *(2021)* Reference-based metrics such as BLEU compare a generated sentence with one human sentence, which is a poor fit for a meaning representation that many sentences can express.
2. **[A Human Evaluation of AMR-to-English Generation Systems](https://md.mova.elamur.ai/free/en/docs/papers/manning-2020-human-evaluation-amr-english-generation/)** *(2020)* Most AMR-to-English systems had been scored only with automatic metrics such as BLEU. The paper runs a new human evaluation of five systems on 100 sentences per system, with 100 human references for comparison. Annotators gave fluency scores (without the input) and adequacy scores (with the AMR), each on a 0–100…
3. **[A Partially Rule-Based Approach to AMR Generation](https://md.mova.elamur.ai/free/en/docs/papers/manning-2019-partially-rule-based-approach-amr/)** *(2019)* The paper generates English from AMR with mostly hand-written rules and only light statistics. Each AMR concept gets a set of candidate realisations: frame concepts become verbal, adjectival and nominal forms (with -ing, -ed, -tion, -ly variants), and special concepts such as named entities and role relations get…

## Co-authors (2)

- [Nathan Schneider](https://md.mova.elamur.ai/free/en/docs/papers/authors/nathan-schneider/) ×2
- [Shira Wein](https://md.mova.elamur.ai/free/en/docs/papers/authors/shira-wein/)
- [← previous Emily Prud'hommeaux](https://md.mova.elamur.ai/free/en/docs/papers/authors/emily-prud-hommeaux/)
- [next → Emmanuele Chersoni](https://md.mova.elamur.ai/free/en/docs/papers/authors/emmanuele-chersoni/)
- [↑ back to Authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/)