VIADAT-SEARCH in connection with VIADAT-REPO enables searching transcripts of oral history recordings. Language analysis has been used to preprocess the recordings, which makes it possible to search the fulltext using multiple criteria, including names, different forms of the same word etc.
Developed in cooperation with ÚSD AV ČR and NFA.
A VIADAT module; the purpose of VIADAT-STAT is statistical analysis of recordings stored by the platform.
Developed in cooperation with ÚSD AV ČR and NFA.
A VIADAT module; the purpose of VIADAT-STAT is statistical analysis of recordings stored by the platform.
Developed in cooperation with ÚSD AV ČR and NFA.
Victor is a web page cleaning tool. It is aimed at removing menu, ads, footers, headers, etc. from HTML web pages, so that only main web page content remains. Victor is based on a conditional random fields algorithm.
Victoria is an on-line HTML web page annotation tool suitable for selecting texts on the web pages. It can be used to mark important/interesting parts of web pages for further processing.
VPS-30-En is a small lexical resource that contains the following 30 English verbs: access, ally, arrive, breathe,
claim, cool, crush, cry, deny, enlarge, enlist, forge, furnish, hail, halt, part, plough, plug, pour, say, smash, smell, steer, submit, swell,
tell, throw, trouble, wake and yield. We have created and have been using VPS-30-En to explore the interannotator agreement potential
of the Corpus Pattern Analysis. VPS-30-En is a small snapshot of the Pattern Dictionary of English Verbs (Hanks and Pustejovsky,
2005), which we revised (both the entries and the annotated concordances) and enhanced with additional annotations. and This work has been partly supported by the Ministry of
Education of CR within the LINDAT-Clarin project
LM2010013, and by the Czech Science Foundation under
the projects P103/12/G084, P406/2010/0875 and
P401/10/0792.
VPS-GradeUp is a collection of triple manual annotations of 29 English verbs based on the Pattern Dictionary of English Verbs (PDEV) and comprising the following lemmas: abolish, act, adjust, advance, answer, approve, bid, cancel, conceive, cultivate, cure, distinguish, embrace, execute, hire, last, manage, murder, need, pack, plan, point, praise, prescribe, sail, seal, see, talk, urge . It contains results from two different tasks:
1. Graded decisions
2. Best-fit pattern (WSD) .
In both tasks, the annotators were matching verb senses defined by the PDEV patterns with 50 actual uses of each verb (using concordances from the BNC [2]). The verbs were randomly selected from a list of completed PDEV lemmas with at least 3 patterns and at least 100 BNC concordances not previously annotated by PDEV’s own annotators. Also, the selection excluded verbs contained in VPS-30-En[3], a data set we developed earlier. This data set was built within the project Reviving Zellig S. Harris: more linguistic information for distributional lexical analysis of English and Czech and in connection with the SemEval-2015 CPA-related task.
A set of corpora for 120 languages automatically collected from wikipedia and the web.
Collected using the W2C toolset: http://hdl.handle.net/11858/00-097C-0000-0022-60D6-1
A tool used to build multilingual corpora from wikipedia. Download the web pages, convert them to plain text, identify language, etc.
A set of 120 corpora collected using this tool is available at https://ufal-point.mff.cuni.cz/xmlui/handle/11858/00-097C-0000-0022-6133-9