| a | 
| Allen's interval algebra | Formal Representation of Temporal Expressions | 
| c | 
| coherent texts | Using Convolutional Neural Networks for Sentiment Attitude Extraction from Analytical Texts | 
| Construction Grammar | Defining discourse formulae: computational approach | 
| Convolutional Neural Networks | Using Convolutional Neural Networks for Sentiment Attitude Extraction from Analytical Texts | 
| corpus-based study | A Corpus-based Study of Japanese Verb Paradigms (Preliminary results) | 
| d | 
| discourse formulae | Defining discourse formulae: computational approach | 
| document retrieval | Three-stage question answering system with sentence ranking | 
| e | 
| Early Irish | Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish | 
| entity extraction | Defining discourse formulae: computational approach | 
| extraction of term definition | Terminological Information Extraction from Russian Scientific Texts: Methods and Applications | 
| f | 
| feature extraction | Irony and sarcasm expression in Twitter | 
| g | 
| Genre Classification | Genre Classification Problem: in Pursuit of Systematics on a Big Webcorpus | 
| glossary creation | Terminological Information Extraction from Russian Scientific Texts: Methods and Applications | 
| h | 
| hybrid machine learning models | An Experimental Study of Hybrid Machine Learning Models for Extracting Named Entities | 
| i | 
| Information Extraction | Evaluating measures of semantic relatedness for Russian language | 
| interval temporal logic | Formal Representation of Temporal Expressions | 
| j | 
| Japanese dictionary | A Corpus-based Study of Japanese Verb Paradigms (Preliminary results) | 
| Japanese language | A Corpus-based Study of Japanese Verb Paradigms (Preliminary results) | 
| l | 
| lemmatisation | Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish | 
| lexico-syntactic patterns | Terminological Information Extraction from Russian Scientific Texts: Methods and Applications | 
| m | 
| machine learning | Defining discourse formulae: computational approach Genre Classification Problem: in Pursuit of Systematics on a Big Webcorpus Verb Construction As A Feature Of Genre Classification | 
| machine-learning-based NER | An Experimental Study of Hybrid Machine Learning Models for Extracting Named Entities | 
| morphological parsing | Automatic morphological analysis  on the material of Russian social media texts | 
| morphological tagging | Automatic morphological analysis  on the material of Russian social media texts | 
| n | 
| Named Entity Recognition | An Experimental Study of Hybrid Machine Learning Models for Extracting Named Entities | 
| Natural Language Processing | Automatic morphological analysis  on the material of Russian social media texts Evaluating measures of semantic relatedness for Russian language Irony and sarcasm expression in Twitter Defining discourse formulae: computational approach Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish | 
| natural language semantics | Formal Representation of Temporal Expressions | 
| neural networks | Automatic morphological analysis  on the material of Russian social media texts An Experimental Study of Hybrid Machine Learning Models for Extracting Named Entities Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish | 
| ngrams corpus | A Corpus-based Study of Japanese Verb Paradigms (Preliminary results) | 
| p | 
| POS tagging | Automatic morphological analysis  on the material of Russian social media texts | 
| q | 
| Question Answering | Three-stage question answering system with sentence ranking | 
| r | 
| ranking system | Three-stage question answering system with sentence ranking | 
| Recurrent Neural Network | Three-stage question answering system with sentence ranking | 
| Rule-based term extraction | Terminological Information Extraction from Russian Scientific Texts: Methods and Applications | 
| s | 
| semantic relatedness | Evaluating measures of semantic relatedness for Russian language | 
| Sentiment Analysis | Using Convolutional Neural Networks for Sentiment Attitude Extraction from Analytical Texts | 
| sequence-to-sequence learning | Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish | 
| social media texts | Automatic morphological analysis  on the material of Russian social media texts | 
| statistical analysis | Irony and sarcasm expression in Twitter | 
| subject index construction | Terminological Information Extraction from Russian Scientific Texts: Methods and Applications | 
| t | 
| taggers for Russian | Automatic morphological analysis  on the material of Russian social media texts | 
| temporal expressions | Formal Representation of Temporal Expressions | 
| text classification | Genre Classification Problem: in Pursuit of Systematics on a Big Webcorpus | 
| u | 
| under-resourced languages | Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish | 
| Universal Dependencies | Automatic morphological analysis  on the material of Russian social media texts Verb Construction As A Feature Of Genre Classification | 
| v | 
| verb conjugation | A Corpus-based Study of Japanese Verb Paradigms (Preliminary results) | 
| verb construction | Verb Construction As A Feature Of Genre Classification | 
| verb paradigm study | A Corpus-based Study of Japanese Verb Paradigms (Preliminary results) | 
| w | 
| web corpus | Genre Classification Problem: in Pursuit of Systematics on a Big Webcorpus | 
| Wikipedia Mining | Evaluating measures of semantic relatedness for Russian language |