--- title: "Christopher Manning — papers and cards" description: "Christopher Manning: 5 paper cards in the Research library (2002–2023), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/christopher-manning/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/christopher-manning/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Christopher Manning # Christopher Manning 5 paper cards in the Research library · 2002–2023 Christopher Manning wrote 5 of the papers Mova reads, in 2002–2023, most of them on [Coreference resolution](https://md.research.elamur.ai/free/en/topics/coreference-resolution/), [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/), [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/); often with [Dan Flickinger](https://md.research.elamur.ai/free/en/authors/dan-flickinger/), [Dan Jurafsky](https://md.research.elamur.ai/free/en/authors/dan-jurafsky/), Danqi Chen. [OpenAlex](https://openalex.org/A5046006076) · [ORCID](https://orcid.org/0000-0001-6155-649X) · [**h-index 139**](https://openalex.org/authors/A5046006076) · [180101 citations](https://openalex.org/authors/A5046006076) · [770 works](https://openalex.org/works?filter=author.id:A5046006076) — 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=Christopher+Manning) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Christopher+Manning) · [dblp](https://dblp.org/search?q=Christopher+Manning) · [ACL Anthology](https://aclanthology.org/search/?q=Christopher+Manning) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Christopher+Manning) Topics: [Coreference resolution](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) 1 · [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) 1 · [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) 1 · [Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/) 1 ## Papers 1. **[PragmatiCQA: A Dataset for Pragmatic Question Answering in Conversations](https://md.research.elamur.ai/free/en/papers/qi-2023-pragmaticqa-dataset-pragmatic-question-answering/)** *(2023)* The dataset has 6,873 question-answer pairs in teacher-student conversations about Fandom wiki topics. For each student question the teacher marks literal answer spans, pragmatic spans that answer the follow-up the student is likely to ask, and a paraphrased final answer. Crowdworkers choose topics of mutual interest… 2. **[Does Universal Dependencies need a parsing representation? An investigation of English](https://md.research.elamur.ai/free/en/papers/silveira-2015-does-universal-dependencies-need-parsing/)** *(2015)* UD makes content words the heads and attaches function words (auxiliaries, copulas, subordinators, adpositions) to them. 3. **[A Fast and Accurate Dependency Parser using Neural Networks](https://md.research.elamur.ai/free/en/papers/missing-2014-chen-fast-accurate-dependency-parser-neural/)** *(2014)* Almost all parsers of the time used millions of sparse indicator features built from hand-made templates, which generalise poorly and make feature extraction the main cost. 4. **[A Multi-Pass Sieve for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/raghunathan-2010-multi-pass-sieve-coreference-resolution/)** *(2010)* `measured` The paper proposes an unsupervised, deterministic coreference system built as a sequence of "sieves": independent rule-based passes applied from the most precise to the least precise. 5. **[The LinGO Redwoods Treebank: Motivation and Preliminary Applications](https://md.research.elamur.ai/free/en/papers/bank-2002-oepen-lingo-redwoods-treebank-motivation-preliminary/)** *(2002)* The paper proposes a treebank that stores full HPSG analyses from a broad-coverage grammar (the LinGO English Resource Grammar) instead of one fixed tree format, so that users can extract the representation they need. ## Co-authors (16) - [Dan Flickinger](https://md.research.elamur.ai/free/en/authors/dan-flickinger/) - [Dan Jurafsky](https://md.research.elamur.ai/free/en/authors/dan-jurafsky/) - Danqi Chen - [Heeyoung Lee](https://md.research.elamur.ai/free/en/authors/heeyoung-lee/) - Jing Huang - Karthik Raghunathan - [Kristina Toutanova](https://md.research.elamur.ai/free/en/authors/kristina-toutanova/) - [Mihai Surdeanu](https://md.research.elamur.ai/free/en/authors/mihai-surdeanu/) - [Natalia Silveira](https://md.research.elamur.ai/free/en/authors/natalia-silveira/) - [Nathanael Chambers](https://md.research.elamur.ai/free/en/authors/nathanael-chambers/) - Nina Du - [Peng Qi](https://md.research.elamur.ai/free/en/authors/peng-qi/) - [Stephan Oepen](https://md.research.elamur.ai/free/en/authors/stephan-oepen/) - [Stuart Shieber](https://md.research.elamur.ai/free/en/authors/stuart-shieber/) - Sudarshan Rangarajan - [Thorsten Brants](https://md.research.elamur.ai/free/en/authors/thorsten-brants/) ## More papers in the library (7) Pages of the Research library: our summary, the ideas, references and who cites each. - [ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts](https://md.research.elamur.ai/free/en/papers/koreeda-2021-contractnli-dataset-document-level-natural/) — Yuta Koreeda, Christopher Manning · 2021 - [The Stanford CoreNLP Natural Language Processing Toolkit](https://md.research.elamur.ai/free/en/papers/manning-2014-stanford-corenlp-natural-language-processing/) — Christopher Manning, Mihai Surdeanu, John Bauer, et al. · 2014 - [Better Word Representations with Recursive Neural Networks for Morphology](https://md.research.elamur.ai/free/en/papers/luong-2013-better-word-representations-recursive-neural/) — Thang Luong, Richard Socher, Christopher Manning · 2013 - [Baselines and Bigrams: Simple, Good Sentiment and Topic Classification](https://md.research.elamur.ai/free/en/papers/wang-2012-baselines-bigrams-simple-good-sentiment/) — Sida Wang, Christopher Manning · 2012 - [Improving Word Representations via Global Context and Multiple Word Prototypes](https://md.research.elamur.ai/free/en/papers/huang-2012-improving-word-representations-global-context/) — Eric Huang, Richard Socher, Christopher Manning, et al. · 2012 - [A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005](https://md.research.elamur.ai/free/en/papers/tseng-2005-conditional-random-field-word-segmenter/) — Huihsin Tseng, Pichuan Chang, Galen Andrew, et al. · 2005 - [Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling](https://md.research.elamur.ai/free/en/papers/finkel-2005-incorporating-non-local-information-into/) — Jenny Rose Finkel, Trond Grenager, Christopher Manning · 2005