We present a machine-readable structured data version of Wiktionary. Unlike previous Wiktionary extractions, the new extractor, Wiktextract, fully interprets and expands templates and Lua modules in Wiktionary. This enables it to perform a more complete, robust, and maintainable extraction. The extracted data is multilingual and includes lemmas, inflected forms, translations, etymology, usage examples, pronunciations (including URLs of sound files), lexical and semantic relations, and various morphological, syntactic, semantic, topical, and dialectal annotations. We extract all data from the English Wiktionary. Comparing against previous extractions from language-specific dictionaries, we find that its coverage for non-English languages often matches or exceeds the coverage in the language-specific editions, with the added benefit that all glosses are in English. The data is freely available and regularly updated, enabling anyone to add more data and correct errors by editing Wiktionary. The extracted data is in JSON format and designed to be easy to use by researchers, downstream resources, and application developers.

In many applications it is important to be able to insert (or delete) keys into a B-tree as a batch, instead of inserting them one by one. Moreover, it may be necessary to search the B-tree concurrently with the batch update. An example of this is a text database system supporting a newspaper house: all words (keys) of each article obtained from a news agency should be inserted at once, and, at the same time, searches for documents containing certain words should be allowed as efficiently as possible. We have designed two solutions to the problem of concurrent batch update. The first solution-implemented in our commercial text database system-optimizes the speed of the batch update, and the second solution optimizes the average search time during the batch update.