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Lemmatization

Lemmatization is a process of determining a base or dictionary form (lemma) for a given surface form. Especially for languages with rich morphology it is important to be able to normalize words into their base forms to better support for example search engines and linguistic studies. Main difficulties in Lemmatization arise from encountering previously unseen words during inference time as well as disambiguating ambiguous surface forms which can be inflected variants of several different base forms depending on the context.

Source: Universal Lemmatizer: A Sequence to Sequence Model for Lemmatizing Universal Dependencies Treebanks

Papers

Showing 6170 of 351 papers

TitleStatusHype
ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared TaskCode0
\'UFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared TaskCode0
DBTagger: Multi-Task Learning for Keyword Mapping in NLIDBs Using Bi-Directional Recurrent Neural NetworksCode0
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical ResourcesCode0
Integrated Sequence Tagging for Medieval Latin Using Deep Representation LearningCode0
CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in MorphologyCode0
Development of a Hindi LemmatizerCode0
NLP-Cube: End-to-End Raw Text Processing With Neural NetworksCode0
CELI: An Experiment with Cross Language Textual Entailment0
CBNU System for SIGMORPHON 2019 Shared Task 2: a Pipeline Model0
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