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| Lexikalische Ersetzung× | Paraphrase Detection× | |
|---|---|---|
| Fachgebiet | Text Mining | Text Mining |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 2007 | — |
| Urheber≠ | McCarthy & Navigli (SemEval shared task, 2007/2009) | — |
| Typ≠ | NLP lexical-level text transformation | NLP sentence-pair classification task |
| Wegweisende Quelle≠ | McCarthy, D. & Navigli, R. (2009). The English Lexical Substitution Task. Language Resources and Evaluation, 43(2), 139-159. link ↗ | Dolan, W. B. & Brockett, C. (2005). Automatically Constructing a Corpus of Sentential Paraphrases. Proceedings of the Third International Workshop on Paraphrasing (IWP). link ↗ |
| Aliasnamen≠ | sözcüksel ikame, Sözcüksel İkame (Lexical Substitution), context-aware synonym replacement, word-level paraphrasing | Parafroz Tespiti (Paraphrase Detection), paraphrase identification, semantic equivalence detection |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | Lexical substitution is a natural-language-processing task — formalised by McCarthy and Navigli through the SemEval shared task series starting in 2007 — that replaces a target word in a sentence with a semantically equivalent alternative that preserves the meaning of the surrounding context. It draws on synonym resources such as WordNet or on distributional word embeddings and masked language models to generate and rank candidate replacements, and is used for text robustness testing, style adaptation, and training-data augmentation. | Paraphrase detection is a natural-language-processing task that decides whether two sentences expressed in different wordings carry the same meaning. The task and its benchmark resources were established by Dolan and Brockett (2005), and it underpins plagiarism detection, question matching, and data deduplication. |
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