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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 261270 of 351 papers

TitleStatusHype
Do we need bigram alignment models? On the effect of alignment quality on transduction accuracy in G2P0
Morphological Analysis for Unsegmented Languages using Recurrent Neural Network Language Model0
Counting What Counts: Decompounding for Keyphrase Extraction0
Lexicon-assisted tagging and lemmatization in Latin: A comparison of six taggers and two lemmatization methods0
Learning Representations for Text-level Discourse Parsing0
IWNLP: Inverse Wiktionary for Natural Language Processing0
Multiple Many-to-Many Sequence Alignment for Combining String-Valued Variables: A G2P Experiment0
A Publicly Available Cross-Platform Lemmatizer for Bulgarian0
Evaluation of the Accuracy of the BGLemmatizer0
JAIST: Combining multiple features for Answer Selection in Community Question Answering0
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