Generative Dependency Language Modeling Using Recurrent Neural Networks

Käesolev magistritöö esitleb meetodit süntaktilise infot kasutamiseks generatiivses keele modelleerimises, kus sõltuvusparseri loogikat laiendatakse, et jooksvalt parseri puhvrisse uusi sõnu genereerida. Selleks kasutatakse sisendina vastaval hetkel pinu tipus olevaid sõnu. Püstitame hüpoteesi, et antud lahendus annab eeliseid kaugete sõltuvuste modelleerimisel. Me implementeerime pakutud keelemudeli ja lähtemudeli ning näeme, et välja pakutud meetod annab märkimisväärselt parema perplexity skoori tulemuse ja seda eriti lausete puhul, mis sisaldavad kaugeid sõltuvusi. Lisaks näitab keelemudelite abil loodud lausete analüüs, et välja pakutud mudel suudab lähtemudeliga võrreldes luua terviklikumaid lauseid.This thesis proposes an approach to incorporating syntactical data to the task of generative language modeling. We modify the logic of a transition-based dependency parser to generate new words to the buffer using the top items in the stack as input. We hypothesize that the approach provides benefits in modeling long-term dependencies. We implement our system along with a baseline language model and observe that our approach provides an improvement in perplexity scores and that this improvement is more significant in modeling sentences that contain longer dependencies. Additionally, the qualitative analysis of the generated sentences demonstrates that our model is able to generate more cohesive sentences

Colour term ‘black’ in Estonian place names

Must ‘black’ is considered to be the most common colour attribute in place names. The article provides a brief overview of must ‘black’ in Estonian place names. The data was obtained from kohanimekartoteek ‘place names card index’ of the Institute of the Estonian Language. In the index there are 1377 slips beginning with (or containing) must ‘black’, discounting within-parish duplicate slips 1081 place names were found. Altogether, 728 different place name variants were discovered. The most frequent occurrences of must in the nominative case were Mustjõgi ‘Black-river’ (frequency = 26), Mustjärv ‘Black-lake’ (22), Mustkivi ‘Black-stone’ (21), Mustoja ‘Black-rivulet’ (18) and Mustmägi ‘Black-hill’ (16). In the genitive case Musta talu ‘Black farm’ (22) was twice as frequent as the next most common, Mustitalu ‘Musti farm’ (11). According to the studied material the most common determinant was talu ‘farm’ (231), followed by mägi ‘hill’ (70), mets ‘forest’ (45) and heinamaa ‘hayfi eld’ (43)

Anestesioloogia

Eesti Arst 2011; 90(7):33

Türgi, eesti ja vene keele värvisõnavara: Millised on põhivärvinimed?

Brent Berlin ja Paul Kay loodud põhivärvinimeteooria sai alguse ideest, et teatud värvinimed on universaalsed. Nad eeldasid, et igas keeles on olemas piiratud arv sõnu värvi tähistamiseks. Neid universaalseid värvinimesid nimetasid nad põhivärvinimedeks. Kas keeles võib olla vaid üks sinine? Eelnevad uurimused kinnitavad, et sinine võib jaguneda kaheks: vene keeles on omaette kategooriad kahele sinise kategooriale, SINIJ ‘sinine’ ja GOLUBOJ ‘helesinine’. Järelikult on ka teisi võimalusi peale üheainsa sinise kategooria. Sinise jagunemine toetab keelelise relatiivsuse teooriat. Kas ka eesti sinine jaguneb (ala)kategooriateks? Kas türgi keeles on samuti kaks sinise kategooriat, nagu eelnevad uurimused (vt Özgen ja Davies 1998) kinnitavad? Vastuse saamiseks küsitleti türgi (N=56), eesti (N=39), ja eestivene (N=30) keelejuhte. Neilt küsiti loetelukatses kõikide värvide kohta, mida nad teavad. Nimeandmiskatses esitati neile ükshaaval värvipaberiga kaetud tahvlikesi küsides: „Mis värvi see stimul on?“. Eesti ja eestivene keelejuhid osalesid loetelu-ja nimeandmiskatse vahe peal ka sorteerimiskatses, kus nad sorteerisid sarnasuse alusel tahvlikesi gruppidesse ja pärast sorteerimist andsid neile gruppidele nimed.The theory of basic colour terms by Brent Berlin and Paul Kay (1969) started with an idea that certain colour categories are universal. They proposed that in every language there is a small, limited amount of words for designating colour. They called these universal colour names basic colour terms. From the theory of basic colour terms and previous research into Turkish, Estonian and Russian basic colour terms arise the questions of whether the behaviour of one blue is universal, and how the category of blue might be divided. There being only one blue category reinforces the universalist view of colour terms, while the appearance of more than one blue category, especially in the sorting task, supports a weak relativist approach. Russian is exceptional because both SINIJ ‘blue’ and GOLUBOJ ‘light blue’ mark blue equally. Are Turkish terms MAVI ‘blue’ and LACIVERT ‘dark blue’ similar? Is Estonian SININE ‘blue’ influenced by Russian and therefore also divided into more than one blue category? Turkish (N=56), Estonian (N=39) and Estonian Russian (N=30) participants were questioned to find an answer to those questions. The participants were asked about all the colours they knew in the list task. In the naming task the participants named coloured stimuli one by one answering the question: “What colour is it?”. Estonian and Estonian Russian participants also completed a sorting task between the list and naming tasks. They sorted coloured stimuli into groups by similarity and after sorting named the groups

Suitability of blue honeysuckle (Lonicera caerulea L.) cultivars of different origin for cultivation in the Nordic-Baltic climate

The rising trend of blue honeysuckle has led to the increase in new plantations and berry production in recent years in Nordic-Baltic region, including Estonia. This crop is naturally distributed in the temperate climate zone of Northern Hemisphere. Estonia is also located in the same climate zone, but differs only from warm maritime air. The main aim of this research was to find out cultivars’ adaptation to the changing weather conditions regarding winter hardiness, fruit weight, yield and occurrence of secondary flowering. The data was recorded from two closely situated plantations in Polli village, Viljandi County, Estonia. Eighteen cultivars of blue honeysuckle with different origin (Russia, Canada, Poland and Czech Republic) were tested. In 2016, greater winter damage was recorded when compared to the period of 2017–2020 with just marginal damage. In conclusion, the Canadian cultivars (‘Borealis’, ‘Indigo Gem’, ‘Indigo Treat’ and ‘Tundra’) and Polish ‘Duet’, presented their best properties and suitability to Estonian climatic conditions