The American National Corpus First Release

By Nancy Ide, Keith Suderman. 2004

96 citations recorded by the source corpus.

The First Release of the American National Corpus (ANC) was made available in mid-fall, 2003. The data includes approximately 11 million words of American English, including written and spoken data and a variety of text types annotated for part of speech and lemma. The corpus is provided in XML format conformant to the XML Corpus Encoding Standard (XCES) (http://www.xml-ces.org), and is distributed in both a stand-off version (where annotation is in an XML document separate from the primary texts) and a merged version (where annotation is included in-line in the texts). The merged version includes annotation for part of speech and lemma produced by the Biber tagger; in stand-off annotation, in addition to the Biber tagging, morpho-syntactic annotations of the data are provided using the CLAWS 5 and 7 tagsets as well as several other tagsets.

Subfields: Artificial Intelligence, Language and Linguistics, Natural Language Processing, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Language and Linguistics

In Natural Language Processing

In Evaluation & Benchmarks

Citations in the corpus

SCROLLS: Standardized CompaRison Over Long Language Sequences (2022, background): “, 2021): A multiplechoice question answering dataset over stories and articles sourced from Project Gutenberg,10 the Open American National Corpus (Fillmore et al., 1998; Ide and Suderman, 2004), and more.”
QuALITY: Question Answering with Long Input Texts, Yes! (2021, background): “Corpus (Fillmore et al., 1998; Ide and Suderman, 2004), and other nonfiction articles taken from The Long+Short,6 Freesouls,7 and the book Open Access (Suber, 2012).”
Integrating Linguistic Resources: The American National Corpus Model (2006, background): “The American National Corpus (ANC) project 1 (Ide and Macleod, 2001; Ide and Suderman, 2004) has released over 20 million words of spoken and written American English, available from the Linguistic Data Consortium.”
Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding (2012, methodology): “Latent Semantic Analysis (LSA) (Deerwester et al., 1990), a very popular technique used in Information Retrieval, performs SVD on a word by document matrix.”
Glen, Glenda or Glendale: Unsupervised and Semi-supervised Learning of English Noun Gender (2009, methodology): “To create our gold-standard gender data, we follow Bergsma (2005) in extracting gender information from the anaphora-annotated portion6 of the American National Corpus (ANC) (Ide and Suderman, 2004).”
Good Question! Statistical Ranking for Question Generation (2010, methodology): “These language models were estimated from the written portion of the American National Corpus Second Release (Ide and Suderman, 2004), which consists of approximately 20 million tokens, using Kneser and Ney (1995) smoothing.”
Neural Unsupervised Domain Adaptation in NLP—A Survey (2020, background): “, 2020), and documenting the known are the first important steps (Bender and Friedman, 2018), as is building broader, more varied corpora (Ide and Suderman, 2004).”