WaG - Word at a Glance

1. Use existing corpus/data search and retrieval software as backend,
2. Obtain and compile information about:
   1. single word,
   2. two or more words compared with each other,
   3. word translation.
3. explore text metadata statistics, time-based trends, word cloud-based data and many more,
4. combine statistics from different corpora,
5. Use results of a resource as an input for other resource.

Currently supported resources

• KonText
• MQuery
• NoSketch Engine
• Treq
• Clarin FCS Core 1
• Datamuse API
• Leipzig Corpora Collection (REST API) (LCC)

	WaG	KonText	MQuery	NoSkE	Treq	Clarin FCS	Datamuse	ElasticSearch	LCC
collocations		⭐	🚧	⭐					⭐
concFilter		⭐
concordance		⭐		⭐		⭐			⭐
freqBar		⭐		⭐
freqComparison		⭐	⭐	⭐
freqPie		⭐		⭐
geoAreas		⭐		⭐
multiWordGeoAreas		⭐		⭐
html		⭐		⭐
matchingDocuments		⭐						⭐
mergeCorpFreq		⭐		⭐
speeches		⭐
syntacticColls			⭐
timeDistrib		⭐	⭐	⭐
multiWordtimeDistrib		⭐		⭐
translations					⭐
treqSubsets					⭐
wordForms	⭐	⭐	🚧
wordFreq	⭐	⭐	🚧
wordSim	⭐		🚧				⭐		⭐

Requirements

WaG is able to run either as a self-hosted application or within a compatible web page. For the self-hosted variant the following is needed:

• Node.JS + NPM package manager
• HTTP proxy server (Nginx, HAProxy, Apache)
• a core word frequency database:
  • CouchDB (data can be generated from a corpus vertical file using CNC-MASM)
  • KorpusDB (CNC's own service)
  • KonText
  • SQLite3

Please refer for more information to the INSTALL.md.

How to cite WaG

Tomáš Machálek (2020): Word at a Glance: Modular Word Profile Aggregator. In: Proceedings of LREC 2020, s. 7011–7016.

@InProceedings{machalek2020lrec,
 author = {Tomáš Machálek},
 title = "{Word at a Glance: Modular Word Profile Aggregator.}",
 booktitle = {Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC 2020)},
 year = {2020},
 publisher = {European Language Resources Association (ELRA)},
 language = {english}
}