Finding Terms in Corpora for Many Languages with the Sketch Engine

The Sketch Engine is a leading corpus tool, widely used in lexicography. Now, at 10 years old, it is mature software. The Sketch Engine website offers many ready-to-use corpora, and tools for users to build, upload and install their own corpora. The paper describes the core functions (word sketches, concordancing, thesaurus). It outlines the different kinds of users, and the approach taken to working with many different languages. It then reviews the kinds of corpora available in the Sketch Engine, gives a brief tour of some of the innovations from the last few years, and surveys other corpus tools and websites.

show abstract

“…A corpus can be collected from the web, using the Corpus Factory (Kilgarriff et al 2010) or TenTen (Jakubíček et al 2013) method.…”

mentioning

confidence: 99%

The Sketch Engine

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this regard, it is a common feature across different languages that specifications do not need to be marked with a connective. For example, in both French (example 5) and German (example 6), specifications without a connective can be left implicit without loss of coherence (all French examples are taken from the French Web corpus frTenTen17; Jakubíček, Kilgarriff, Kovář, Rychlý & Suchomel, 2013; all German examples are taken from the German corpus German WebTenTen13, Jakubíček et al, 2013; by using the search engine SketchEngine; Kilgarriff, Baisa, Bušta, Jakubíček, Kovář, Michelfeit, et al, 2014) . It is, however, also possible in both languages to explicitly mark specifications.…”

Section: Research Backgroundmentioning

confidence: 99%

Processing clause-internal discourse relations in a second language

Wetzel

Crible²,

Zufferey

2022

JSLS

View full text Add to dashboard Cite

Coherence relations are expressed differently across languages, often leading to language learners misusing discourse connectives. We argue that the ability to detect these errors crucially depends on the coherence relation under scrutiny, as errors may remain unnoticed when the relation is clause-internal and marked with a highly optional connective. We focus, therefore, on specifications, a relation that German-speaking learners sometimes struggle to correctly indicate when writing in French. We assessed whether non-native readers detect this error and show preferences for either explicit or implicit marking of specifications. Findings show that non-native speakers were generally able to detect the error in a sentence-evaluation task but did not react to it in a self-paced-reading task, contrary to native speakers. They also judged implicit specifications as more correct than explicitly marked specifications. We conclude that non-native speakers do not always benefit from connectives during text processing, especially when they are highly optional.

show abstract

“…Sketch Engine is named after one of its key features-word sketches. It employs a contrastive two-step approach to terminology extraction-first the grammatical validity of a phrase (unithood) is assessed using the term grammar, next the normalized frequencies of TCs from the focus corpus are contrasted (termhood) with those in the reference corpus [31] by using the "Simple Math" (with an add-N parameter of one) statistics [32]. Sketch Engine implements ATE as two separate processes, dependent on the user needs-keywords extraction and multiwords extraction.…”

Section: Automatic Extraction Taskmentioning

confidence: 99%

Application-based Evaluation of Automatic Terminology Extraction

Bakarić¹,

Babić²,

Matetić³

2021

IJACSA

View full text Add to dashboard Cite

The aim of this paper is to evaluate performance of several automatic term extraction methods which can be easily utilized by translators themselves. The experiments are conducted on German newspaper articles in the domain of politics on the topic of Brexit. However, they can be easily replicated on any other topic or language as long as it is supported by all three tools used. The paper first provides an extensive introduction into the field of automatic terminology extraction. Next, selected terminology extraction methods are assessed using precision with respect to the gold standard compiled on the same corpus. Moreover, the corpus has been completely annotated to allow for the calculation of recall. The effects of using five cut-off points are examined in order to find an optimal value which should be used in translation practice.

show abstract

Finding Terms in Corpora for Many Languages with the Sketch Engine

Cited by 60 publications

References 2 publications

The Sketch Engine

The Sketch Engine

Processing clause-internal discourse relations in a second language

Application-based Evaluation of Automatic Terminology Extraction

Contact Info

Product

Resources

About