--- title: "Eugene Charniak — papers and cards" description: "Eugene Charniak: 4 paper cards in the Research library (2004–2006), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/eugene-charniak/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/eugene-charniak/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Eugene Charniak # Eugene Charniak 4 paper cards in the Research library · 2004–2006 Eugene Charniak wrote 4 of the papers Mova reads, in 2004–2006, most of them on [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/), [Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/); often with [Mark Johnson](https://md.research.elamur.ai/free/en/authors/mark-johnson/), [David McClosky](https://md.research.elamur.ai/free/en/authors/david-mcclosky/), Eric K. Ringger. [OpenAlex](https://openalex.org/A5005380528) · [**h-index 56**](https://openalex.org/authors/A5005380528) · [12874 citations](https://openalex.org/authors/A5005380528) · [218 works](https://openalex.org/works?filter=author.id:A5005380528) — 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=Eugene+Charniak) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Eugene+Charniak) · [dblp](https://dblp.org/search?q=Eugene+Charniak) · [ACL Anthology](https://aclanthology.org/search/?q=Eugene+Charniak) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Eugene+Charniak) Topics: [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) 1 · [Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/) 1 ## Ideas Mova took (1) From the ideas ledger: an idea tried, kept or queued, or measured with no gain, and what it gave. - **kept** — Oracle gap from en beam-curve: report the oracle LAS of the beam against the 1-best LAS at beam sizes 1, 2, 4, 8 and 16 on EWT dev; a large gap, as the paper shows for 50-best, says a reranker has room to help. *([Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative…](https://md.research.elamur.ai/free/en/papers/narrative-2005-charniak-coarse-fine-n-best-parsing/) · beam oracle EWT dev our tags: width 1/2/4/8/16 1-best 75.27/78.12/78.83/79.39/79.24, oracle 75.27/79.67/82.20/84.14/85.52 (gap 4.74 at 8); commit 3ba5388e8)* ## Papers 1. **[Effective Self-Training for Parsing](https://md.research.elamur.ai/free/en/papers/aclbulk-2006-mcclosky-effective-self-training-parsing/)** *(2006)* Self-training of parsers was thought to fail because the parser's own errors are amplified. This paper shows that it works when the self-labelled trees come from a two-stage parser and reranker: the 50-best parses of 24 million unlabelled News sentences are reranked, and the reranker's best tree is added to the Wall… 2. **[Reranking and Self-Training for Parser Adaptation](https://md.research.elamur.ai/free/en/papers/aclbulk-2006-mcclosky-reranking-self-training-parser-adaptation/)** *(2006)* Parsers trained on the Wall Street Journal lose much accuracy on other genres: the standard parser scores 89.7% on WSJ but only 82.9% on the Brown corpus. 3. **[Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking](https://md.research.elamur.ai/free/en/papers/narrative-2005-charniak-coarse-fine-n-best-parsing/)** *(2005)* `1 idea kept` A discriminative reranker needs a good list of candidate parses for each sentence. The authors produce 50-best lists with a coarse-to-fine generative parser: a coarse pass prunes the chart, and a finer pass scores the surviving parses, which gives lists of much higher quality than the usual n-best output. A MaxEnt… 4. **[Using the Penn Treebank to Evaluate Non-Treebank Parsers](https://md.research.elamur.ai/free/en/papers/bank-2004-ringger-penn-treebank-evaluate-non-treebank/)** *(2004)* The question is how to compare a parser that was never trained on the Penn Treebank (NLPWin, built at Microsoft Research) with Treebank-trained parsers such as Charniak's, when the two attach modifiers in a different order and use different brackets. ## Co-authors (6) - [Mark Johnson](https://md.research.elamur.ai/free/en/authors/mark-johnson/) ×3 - [David McClosky](https://md.research.elamur.ai/free/en/authors/david-mcclosky/) ×2 - Eric K. Ringger - Hisami Suzuki - Lucy Vanderwende - Robert C. Moore ## More papers in the library (7) Pages of the Research library: our summary, the ideas, references and who cites each. - [The Same-Head Heuristic for Coreference](https://md.research.elamur.ai/free/en/papers/elsner-2010-same-head-heuristic-coreference/) — Micha Elsner, Eugene Charniak · 2010 - [EM Works for Pronoun Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/charniak-2009-em-works-pronoun-anaphora-resolution/) — Eugene Charniak, Micha Elsner · 2009 - [Coreference-inspired Coherence Modeling](https://md.research.elamur.ai/free/en/papers/elsner-2008-coreference-inspired-coherence-modeling/) — Micha Elsner, Eugene Charniak · 2008 - [A Unified Local and Global Model for Discourse Coherence](https://md.research.elamur.ai/free/en/papers/elsner-2007-unified-local-global-model-discourse/) — Micha Elsner, Joseph Austerweil, Eugene Charniak · 2007 - [Immediate-Head Parsing for Language Models](https://md.research.elamur.ai/free/en/papers/charniak-2001-immediate-head-parsing-language-models/) — Eugene Charniak · 2001 - [A Maximum-Entropy-Inspired Parser](https://md.research.elamur.ai/free/en/papers/charniak-2000-maximum-entropy-inspired-parser/) — Eugene Charniak · 2000 - [A Statistical Approach to Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/ge-1998-statistical-approach-anaphora-resolution/) — Niyu Ge, John Hale, Eugene Charniak · 1998