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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

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Showing 201–225 of 351 papers

TitleStatusHype
ECNU at SemEval-2017 Task 4: Evaluating Effective Features on Machine Learning Methods for Twitter Message Polarity Classification—0
Context Sensitive Lemmatization Using Two Successive Bidirectional Gated Recurrent Networks—0
SU-RUG at the CoNLL-SIGMORPHON 2017 shared task: Morphological Inflection with Attentional Sequence-to-Sequence Models—0
Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similarity—0
Exploring Properties of Intralingual and Interlingual Association Measures Visually—0
Services for text simplification and analysis—0
Multilingwis ^2 -- Explore Your Parallel Corpus—0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
Adapting a State-of-the-Art Tagger for South Slavic Languages to Non-Standard Text—0
The First Cross-Lingual Challenge on Recognition, Normalization, and Matching of Named Entities in Slavic Languages—0
Gender Profiling for Slovene Twitter communication: the Influence of Gender Marking, Content and Style—0
A data-driven approach to verbal multiword expression detection. PARSEME Shared Task system description paper—0
Spelling Correction for Morphologically Rich Language: a Case Study of Russian—0
Distributional regularities of verbs and verbal adjectives: Treebank evidence and broader implications—0
Improving Neural Translation Models with Linguistic Factors—0
ENIAM: Categorial Syntactic-Semantic Parser for Polish—0
YAMAMA: Yet Another Multi-Dialect Arabic Morphological Analyzer—0
Automatic Translation of English Text to Indian Sign Language Synthetic Animations—0
Acquisition of semantic relations between terms: how far can we get with standard NLP tools?—0
The Power of Language Music: Arabic Lemmatization through Patterns—0
The impact of simple feature engineering in multilingual medical NER—0
Improving the Morphological Analysis of Classical Sanskrit—0
Towards error annotation in a learner corpus of Portuguese—0
LAMB: A Good Shepherd of Morphologically Rich Languages—0
Still not there? Comparing Traditional Sequence-to-Sequence Models to Encoder-Decoder Neural Networks on Monotone String Translation Tasks—0
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