---
title: "A Semantic Concordance — Miller 1993"
description: "The authors propose the notion of a \"semantic concordance\". 8 references, cited by 293 papers here."
authors: ["George A. Miller", "Claudia Leacock", "Randee Tengi", "Ross T. Bunker"]
year: 1993
venue: "Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993"
source: "https://aclanthology.org/H93-1061/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/miller-1993-semantic-concordance/"
---
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# A Semantic Concordance

**Authors:** [George A. Miller](https://md.research.elamur.ai/free/en/authors/george-a-miller/), [Claudia Leacock](https://md.research.elamur.ai/free/en/authors/claudia-leacock/), Randee Tengi and Ross T. Bunker · **Year:** 1993 · **Venue:** Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993 · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/H93-1061/) · [PDF](https://aclanthology.org/H93-1061.pdf)

**Citations:** [293](https://md.research.elamur.ai/free/en/papers/miller-1993-semantic-concordance/cited-by/) in our library, of the 140,884 papers whose bibliographies we read

## Summary

The authors propose the notion of a "semantic concordance". This is a resource in which a corpus and a dictionary are combined so that each content word occurring in the corpus is connected to the lexicon sense it expresses. Such a resource can be used both as a corpus with syntactic and semantic annotation and as a dictionary in which many definitions are accompanied by real usage examples. The aim of the work is to create a basis for research on the automatic discrimination of word senses in context (word sense disambiguation). The Brown Corpus is taken as the text and WordNet as the lexicon. Annotators manually assign semantic tags, i.e., pointers to a synset, in a dedicated interface, ConText. Before this, the text is preprocessed: parts of speech are tagged, and collocations and proper names are joined. Annotation proceeds sequentially, word by word. This immediately reveals which words or senses are missing from WordNet, so the dictionary is improved in parallel with the annotation. WordNet's coverage of the annotated texts reached slightly over 96%. The authors show that such a hybrid resource is useful beyond WSD as well: in teaching English as a foreign language, for statistics on sense frequency, for studying the co-occurrence of senses in topical contexts, and for testing reading comprehension.

## Key points

- **Components:** the Brown Corpus, i.e., 500 passages of approximately 2,000 words each, totaling about 1,014,000 words of American English across various genres. The lexicon is WordNet.
- **Size of WordNet at the time:** over 83,800 entries, of which about 43% are collocations. Over 63,300 synsets, approximately 63% of which have definitions. Over 118,600 word–concept pairs and over 87,600 semantic relations. The dictionary was growing by almost 1,000 concepts each month.
- **ConText:** an interface for X-windows. It displays a word in context together with all synsets for the corresponding part of speech, and the annotator selects the appropriate sense. Only nouns, verbs, adjectives, and adverbs are annotated, which amounts to approximately half of the word tokens in the corpus.
- **Two approaches to annotation:** "targeted" (takes a single polysemous word and annotates all its occurrences) and "sequential" (proceeds through the text from beginning to end). The sequential approach was chosen as the main one because it quickly reveals gaps in the dictionary. Average WordNet coverage with it slightly exceeds 96%.
- **Proposed applications:** teaching English as a foreign language, counting the most frequent senses (for example, the synset {year} occurred 172 times), data on sense co-occurrence instead of artificial topical classifications, psychometric tests of text comprehension.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [AI & machine learning](https://md.research.elamur.ai/free/en/shelves/ai/)

## Cite

Cite as: George A. Miller, Claudia Leacock, Randee Tengi and Ross T. Bunker. 1993. A Semantic Concordance. Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{miller1993semantic,
  title = {{A Semantic Concordance}},
  author = {George A. Miller, Claudia Leacock, Randee Tengi and Ross T. Bunker},
  booktitle = {Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993},
  year = {1993},
  url = {https://aclanthology.org/H93-1061/}
}
```

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## References

8 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Miller, G. A. (ed.), WordNet: An on-line lexical database. International Journal of Lexicography (special issue), 3(4):235-312, 1990. [find](https://scholar.google.com/scholar?q=Miller%2C+G%2E+A%2E+%28ed%2E%29%2C+WordNet%3A+An+on%2Dline+lexical+database%2E+International+Journal+of+Lexicography+%28special+issue%29%2C+3%284%29%3A235%2D312%2C+1990%2E)
2. Miller, G. A. and Fellbaum, C. Semantic networks of English. Cognition (special issue), 41(1-3):197-229, 1991. [find](https://scholar.google.com/scholar?q=Miller%2C+G%2E+A%2E+and+Fellbaum%2C+C%2E+Semantic+networks+of+English%2E+Cognition+%28special+issue%29%2C+41%281%2D3%29%3A197%2D229%2C+1991%2E)
3. Ku~era, H. and Francis, W. N. Computational analysis of present-day American English. Providence, RI: Brown University Press, 1967. [find](https://scholar.google.com/scholar?q=Ku%7Eera%2C+H%2E+and+Francis%2C+W%2E+N%2E+Computational+analysis+of+present%2Dday+American+English%2E+Providence%2C+RI%3A+Brown+University+Press%2C+1967%2E)
4. Francis, W. N. and Ku~era, H. Frequency analysis of English Usage: Lexicon and Grammar. Boston, MA: Houghton Mifflin, 1982. [find](https://scholar.google.com/scholar?q=Francis%2C+W%2E+N%2E+and+Ku%7Eera%2C+H%2E+Frequency+analysis+of+English+Usage%3A+Lexicon+and+Grammar%2E+Boston%2C+MA%3A+Houghton+Mifflin%2C+1982%2E)
5. Leacock, C. ConText: A toot for semantic tagging of text: User's guide. Cognitive Science Laboratory, Princeton University: CSL Report No. 54, February 1993. [find](https://scholar.google.com/scholar?q=Leacock%2C+C%2E+ConText%3A+A+toot+for+semantic+tagging+of+text%3A+User%27s+guide%2E+Cognitive+Science+Laboratory%2C+Princeton+University%3A+CSL+Report+No%2E+54%2C+February+1993%2E)
6. Brill, E. A simple rule-based part of speech tagger. In Proceedings of Speech and Natural Language Workshop, 112-116, February 1992. San Mateo, CA: Morgan Kaufman. [our card](https://md.research.elamur.ai/free/en/papers/brill-1992-simple-rule-based-part-speech/)
7. Landauer, S. I. Dictionaries: The art and craft of lexicography. New York: Scribner's, 1984. [find](https://scholar.google.com/scholar?q=Landauer%2C+S%2E+I%2E+Dictionaries%3A+The+art+and+craft+of+lexicography%2E+New+York%3A+Scribner%27s%2C+1984%2E)
8. Chapman, R. L. (ed.) Roget's International Thesaurus, (5th edition). New York: HarpcrCollins, 1992. [find](https://scholar.google.com/scholar?q=Chapman%2C+R%2E+L%2E+%28ed%2E%29+Roget%27s+International+Thesaurus%2C+%285th+edition%29%2E+New+York%3A+HarpcrCollins%2C+1992%2E)
