Glossary

(also referred to as word_lc, word lowercase or word form lowercase) is a positional attribute assigned to of each token in the corpus. The lc attribute is a lowercased version of the word attribute: John becomes john, Apple becomes apple, BE becomes be. The lc attribute makes the upper case and lowercase version of each token identical. The lc attribute is used for case insensitive searching and analysis see also word form lemma (lowercase) list of attributes

A collection of texts produced by learners of a language used to study errors and mistakes made by learners of languages. Learner corpora in Sketch Engine can use both error and correction annotation. A special search interface is available to search by the former or the latter or both. see also Setting up a learner corpus

Lemma is a positional attribute. It is the basic form of a word, typically the form found in dictionaries. A lemmatized corpus allows for searching for the basic form and include all forms of the word in the result, e.g. searching for lemma go will find go, goes, went, going, gone. Lemma in Sketch Engine is case sensitive so City and city are two different lemmas (City = the City of London; city = a common noun). The lemma of the first word of a sentence is always lowercase. Therefore, the search for lemma city will also find City but only in if City appears at the beginning of a sentence. A wordlist of lemmas is a frequency list where all of go, went, gone, goes, going are counted together and listed as go. A lemma search of go will find all of go, went, gone, goes, going. The concept of the lemma is not always clearly defined and may differ between languages (or even between two corpora in the same language). For example, in Sketch Engine, many, more, most are three different lemmas in English. On the other hand, in Czech, the same adjective which is also irregular mnoho, více, nejvíce share the same lemma hodně. The situation is even more complex with agglutinating languages such as Turkish, Hungarian or Japanese where it may not be easy to decide how many affixes should be removed to produce a lemma. The term stem often replaces the term lemma but stem often refers to the very core part of the word while several lemmas may share the same stem. In Sketch Engine, all corpora in the same language are processed using the same tools and therefore have the same lemmatization. Rare exceptions exist if the corpus was acquired from external sources including the original lemmatization. See also lemma-lc word form lempos list of attributes

lemma_lc is a positional attribute. It is a lemma converted to lowercase.   apple and Apple are treated as the same thing. It is used for case insensitive searching and case insensitive analysis. see lemma

Lemmatization is a process of assigning a lemma to each word form in a corpus using an automatic tool called a lemmatizer. Lemmatization bring the benefit of searching for a base form of a word and getting all the derived forms in the result, e.g. searching for go will also find goes, went, gone, going. See also PoS tagger stemming

Lempos is a positional attribute, i.e. an attribute assigned to each token in the corpus.  It is a combination of lemma and part of speech (pos) consisting of the lemma, hyphen and a one-letter abbreviation of the part of speech, eg. go-v, house-n. The part of speech abbreviations differ between corpora. Lempos is case sensitive, house-n is different from House-n. see also lempos_lc lemma list of attributes

lempos_lc is a positional attribute. It is a lowercased version of lempos. All uppercase letters are converted to lowercase, thus House-n becomes identical with house-n. It is used for case insensitive searching and analysis. see also lempos list of attributes

a function of parameters of a statistical model, it plays a key role in statistical inference and is the basis for the log-likelihood function. see Statistics in Sketch Engine

one of the functions used in computed statistics of Sketch Engine. It is the association measures based on the likelihood function, using in tests for significance (see the log-likelihood calculator and more details)

a statistic measure for identifying co-occurrence (=two items appearing together). Sketch Engine uses it to identify collocations. It expresses the typicality (or strength) of the collocation. It is used in the word sketch feature and also when computing collocations from a concordance. It is only based on the frequency of the node and the collocate and the frequency of the whole collocation (co-occurrence of the node and collocate). logDice is not affected by the size of the corpus and, therefore, can be used to compare scores between different corpora. logDice is the preferred statistic measure for large corpora. The other traditional measures take corpus size into account and the enormous size of the current multi-billion-word corpora skews the score so much as to make them impractical. In bilingual terminology extraction LogDice is also used in bilingual term extraction to identify the most probable translation. In detail A detailed explanation for non-statisticians and non-mathematicians is published in this blog post: Most frequent or most typical collocations?     see also logDice in Statistics used in Sketch Engine A Lexicographer-Friendly Association Score (paper) T-score MI score

The longest-commonest match (LCM) was coined by Adam Kilgarriff to name the most common realisation of a collocation, i.e. the chunk of language in which the collocation appears most frequently. The longest-commonest match is part of the word sketch result screen to facilitate the understanding of how the collocation typically behaves. The longest-commonest match can reveal some important phraseological or idiomatic behaviour of the collocation. For example, cat frequently cooccurs with predator. The LCM, i.e. the most frequent representation of this collocation, is cats are predators which indicates that in general statements, plurals are preferred as opposed to A cat is a predator. Similarly, the LCM for anybody and disagree is anybody who disagrees with suggesting that this construction is the preferred option an not the -ing form as in anybody disagreeing with. related paper

Longtag is a detailed part-of-speech tag which usually contains more information than tag. Some corpora have tags containing only basic information on parts of speech and also attribute longtags consist of detailed grammatical information such as case, number, gender, etc. The longtangs are available in Estonian corpus etTenTen or Turkis corpus trTenTen.