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Start Over Rights http://creativecommons.org/licenses/by/4.0/ Type lexicalConceptualResource Type other Harvested from LINDAT/CLARIAH-CZ repository

1. Motion Encoding Lexicalization Patterns: Portuguese and English Learners

Creator:
Costa-Silva, Jean
Publisher:
University of Georgia
Type:
text, other, and lexicalConceptualResource
Subject:
motion encoding, language acquisition, Portuguese, English, and lexicalization patterns
Language:
English
Description:
General Information: Data collector: Jean Costa Silva (University of Georgia) Date of collection: September-December 2022 Manner of collection: Online questionnaire via Qualtrics Funding: No
Rights:
Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

2. Semantic Difference Keywords - word2vec embeddings

Creator:
Gribomont, Isabelle
Publisher:
Cental (UCL)
Type:
text, other, and lexicalConceptualResource
Subject:
semantic change and lexical semantics
Language:
Spanish
Description:
Embeddings from word2vec model described in "From Diachronic to Contextual Lexical Semantic Change: Introducing Semantic Difference Keywords (SDKs) for Discourse Studies". Full reference TBC.
Rights:
Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

3. VPS-GradeUp (2016-10-10)

Creator:
Baisa, Vít, Cinková, Silvie, Krejčová, Ema, and Vernerová, Anna
Publisher:
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:
text, other, and lexicalConceptualResource
Subject:
Pattern Dictionary of English Verbs, usage patterns, lexical semantics, dictionaries, clustering, Corpus Pattern Analysis, verbs, graded decisions, Likert scale, and Word Sense Disambiguation
Language:
English
Description:
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.
Rights:
Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB