Estonian language

Kopeerimine ja printimine lubatudhttp://www.ester.ee/record=b2323785*es

Ethnic Russian Minority in Estonia

The article examines the position of Russians in Estonia and their relation with ethnic Estonians. The author analyzes models of the society integration introduced by Tallinn after 1991. The results raise questions regarding language education in Estonia, the proficiency level of Estonian is getting widely known by Russians, but on the other hand, there is still a significant part of the population that cannot communicate in Estonian. Those who have a good command of Estonian tend to be better integrated and to coexist with both Estonians and Russians. Russians living in Estonia are supposed to be equally involved in social and political life of the state. The potential of all residents has to be effectively and considerably used, especially when the number of population is decreasing. The position of Russians in Estonia is a major domestic and bilateral issue in the relations with the Russian Federation

Estonian language technology Anno 2009

Proceedings of the NODALIDA 2009 workshop Nordic Perspectives on the CLARIN Infrastructure of Language Resources. Editors: Rickard Domeij, Kimmo Koskenniemi, Steven Krauwer, Bente Maegaard, Eiríkur Rögnvaldsson and Koenraad de Smedt. NEALT Proceedings Series, Vol. 5 (2009), 21-26. © 2009 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/9207

Russian-Estonian Relations After 2007: Current Status and Development Prospects

The article highlights the major points that have influenced relations between Russia and Estonia after 2007. These relations were rather poor during the post-Soviet period. The number of Russian people who lived in Estonia after gaining independence in 1991 exceeded 30%, which resulted in the very keen interest of Russia in Estonian politics. April 2007 created a new reality for relations between the countries. The decision to move the statues of Second World War Soviet soldiers from main squares to cemeteries provoked negative reactions from Russians living in Estonia, but also infuriated leaders of the Russian government. As a consequence there were harsh verbal attacks from Moscow, the Estonian ambassador to Moscow was harassed, cyberspace attacks took place and traffic over the bridge in Narva, which is a key highway from Russia, was blocked. The Estonian authorities know there is no point in maintaining conflict with Russia. The President of Estonia, Toomas Hendrik Ilves, has stressed that Estonia's relationship with its biggest neighbour, Russia, can only get better. Russia plays an incredibly important role in the Estonian economy and tourist industry, according to Andrus Ansip, the Prime Minister of Estonia

Sõnatähenduste normimise traditsioon ja selle murdmine eesti keelekorralduses

Eesti keelekorralduse traditsioon normida õigekeelsussõnaraamatuga (ÕS) üldkeele sõnade tähendusi on pikalt kujundanud ühiskonna arusaama (eesti) keele toimimisest. Alates 1980. aastatest on keelekorralduses sõnade tähendusi normimise asemel „leebemalt“ suunatud, neid kirjakeelde sobimatuks peetud ja nende kohta soovitusi antud (mh ÕSides 1999–2018). Artiklis anname ülevaate eesti keele sõnatähenduste normimise ajaloost üldisemalt alates 19. sajandi teisest poolest, analüüsides olulisemaid keelekorraldusega seotud väljaandeid. Teeme üldistusi ja järeldusi sõnatähenduste normimise kohta, tuginedes oma varasemale sõnatähendustega seotud uurimistööle: kasutuspõhise keeleteooria ja korpuslingvistika süvenemisega eesti keeleteaduses on ka keelekorralduses jõutud arusaamale, et tähendused ei püsi sõnaraamatus kinni: (uue) tähenduse kasutusse jäämine sõltub keelesisestest ja -välistest teguritest, mitte ÕSist. Abstract. Lydia Risberg, Margit Langemets: Breaking the tradition of standardizing word meanings in Estonian language planning. The tradition of the Estonian language planning to standardize the meanings of general language through the formal Dictionary of Standard Estonian (DSE) has long influenced society’s understanding of how (Estonian) language works. Since the 1980s, instead of standardizing the meanings, the language planning has been more “lenient”, considering certain meanings inappropriate for the standard language and making recommendations on them (e.g. in the DSE 1999–2018). In this article, we will give an overview of the history of the standardization of word meanings in the Estonian language planning since the second half of the 19th century, analyzing the most important publications related to it. We draw generalizations and conclusions about the standardization of meanings based on our earlier research on word meanings: with the deepening of usage-based linguistics and corpus linguistics in Estonian linguistics, the understanding has been reached in language planning that meanings do not remain fixed in the dictionary: the (new) meaning’s survival in use depends on internal and external factors, not on the formal DSE

Labour Market Flexibility in Estonia: What More Can Be Done?

In mid-2008, high employment and low unemployment rates characterised the Estonian labour market in comparison with the average of the EU15 countries. While aggregate outcomes improved during 2000 07, large inequalities persisted across regions, ethnic groups, and workers with different skill levels. As Estonia entered recession in 2008, the unemployment rate almost doubled between the 2nd and the 4th quarter, and is expected to rise further in 2009 and 2010. More flexible labour markets will be a key adjustment mechanism during the recession as well as in the medium term if Estonia is to become a knowledge based economy. Given the currency board arrangement and low synchronisation with the euro area, flexibility is also needed to cushion asymmetric shocks. In December 2008, parliament adopted the new Employment Contract Act, deregulating employment protection while increasing income security of the unemployed. This paper discusses options for removing the remaining barriers that impede worker reallocation across jobs, sectors, and regions into more productive activities.http://deepblue.lib.umich.edu/bitstream/2027.42/64375/1/wp964.pd

Labor Supply of Married Females in Estonia

In this paper we estimate the labor supply function for married females in Estonia. Particularly, we are interested in determining the elasticities of the weekly supply of hours with respect to hourly wage rates and with respect to nonlabor income. We adopt the two-step estimation procedure. In the first step, we obtain parameter estimates of the self-selection corrected wage equation. At this stage, we document the absence of the sample selection bias in our data as well as the significant negative effect of nonproficiency in the Estonian language on the hourly wage rate. In the second step, the labor supply function is estimated using the Tobit model, where the predictions from the wage equation substitute for the market wage rates for all individuals. We find that the wage elasticity of hours supplied per week is positive (0.53), while at the same time the nonlabor income effect is insignificant.Female Labor Supply, Transition Economics, Estonian Labor Market

Named Entity Recognition for the Estonian Language

Käesoleva töö raames uuriti eestikeelsetes tekstides nimega üksuste tuvastamise probleemi (NÜT) kasutades masinõppemeetodeid. NÜT süsteemi väljatöötamisel käsitleti kahte põhiaspekti: nimede tuvastamise algoritmi valikut ja nimede esitusviisi. Selleks võrreldi maksimaalse entroopia (MaxEnt) ja lineaarse ahela tinglike juhuslike väljade (CRF) masinõppemeetodeid. Uuriti, kuidas mõjutavad masinõppe tulemusi kolme liiki tunnused: 1) lokaalsed tunnused (sõnast saadud informatsioon), 2) globaalsed tunnused (sõna kõikide esinemiskontekstide tunnused) ja 3) väline teadmus (veebist saadud nimede nimekirjad). Masinõppe algoritmide treenimiseks ja võrdlemiseks annoteeriti käsitsi ajakirjanduse artiklitest koosnev tekstikorpus, milles märgendati asukohtade, inimeste, organisatsioonide ja ehitise-laadsete objektide nimed. Eksperimentide tulemusena ilmnes, et CRF ületab oluliselt MaxEnt meetodit kõikide vaadeldud nimeliikide tuvastamisel. Parim tulemus, 0.86 F1 skoor, saavutati annoteeritud korpusel CRF meetodiga, kasutades kombinatsiooni kõigist kolmest nime esitusvariandist. Vaadeldi ka süsteemi kohanemisvõimet teiste tekstižanridega spordi domeeni näitel ja uuriti võimalusi süsteemi kasutamiseks teistes keeltes nimede tuvastamisel.In this thesis we study the applicability of recent statistical methods to extraction of named entities from Estonian texts. In particular, we explore two fundamental design challenges: choice of inference algorithm and text representation. We compare two state-of-the-art supervised learning methods, Linear Chain Conditional Random Fields (CRF) and Maximum Entropy Model (MaxEnt). In representing named entities, we consider three sources of information: 1) local features, which are based on the word itself, 2) global features extracted from other occurrences of the same word in the whole document and 3) external knowledge represented by lists of entities extracted from the Web. To train and evaluate our NER systems, we assembled a text corpus of Estonian newspaper articles in which we manually annotated names of locations, persons, organisations and facilities. In the process of comparing several solutions we achieved F1 score of 0.86 by the CRF system using combination of local and global features and external knowledge