A new ParlaMint corpus for Hungarian 30m tokens of annotated parliamentary data

Parliamentary data constitute a rich source for research for academic fields in the social sciences and humanities (SSH). To facilitate such research, comparable, high-quality parliamentary corpora are needed. The ParlaMint project, funded by CLARIN-ERIC, aims to create such corpora for languages spoken in European parliaments in a shared framework consisting of uniform encoding schemas, metadata structure, and Universal Dependencies-type linguistic annotation. The newly built Hungarian corpus of ParlaMint II focuses on the minutes of the Hungarian National Assembly between May 2014 and June 2022 and can be considered a major improvement from the Hungarian corpus of ParlaMint I. It has a wider time frame, more extensive metadata on speakers and their affiliations, and more sophisticated linguistic analysis than what was available in ParlaMint I. The Hungarian ParlaMint II corpus is openly available, just as all the ParlaMint corpora for other languages. Some potential applications of ParlaMint corpora in SSH research are also discussed

HuLU : magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából

A cikkben bemutatjuk a neurális nyelvmodellek nyelvértésének mérésére, kiértékelésére és a modellek összehasonlítására létrehozott adatbázisunkat. Az angol példát (GLUE – Wang és mtsai, 2018 –, illetve SuperGLUE – Wang és mtsai, 2020 – benchmarkok) követve, de a redundanciát mellőzve kiválasztottunk 13 olyan specifikus feladatot és az ehhez kapcsolódó alkorpuszokat, amelyekkel a neurális modellek teljesítménye mérhető. Mivel az angol benchmarkokban szereplő korpuszok közül egyik sem létezik a magyarra, ezeket megtervezzük, megépítjük, majd egységes tesztelési keretbe foglalva közrebocsátjuk ezeket

Jönnek a nagyok! : BERT-Large, GPT-2 és GPT-3 nyelvmodellek magyar nyelvre

Az utóbbi években rendkívüli mértékben felgyorsult a Transformer alapú nyelvmodellek méretének a növekedése. A globális technológiai cégek nagyobbnál nagyobb modelleket tanítanak, amelyek óriási erőforrást és tanítóanyagot igényelnek. Ezekkel a kísérletekkel azt próbálják bebizonyítani, hogy megfelelően nagy méretű modellek, megfelelően sok tanítóanyaggal képesek önmagukban akár finomhangolás nélkül bármilyen nyelvtechnológiai feladatot megoldani. Ebbe a versenybe nem igazán lehetséges beszállni, de arra van lehetőség, hogy az árnyékukban elkezdjünk kísérleteket végezni a nagyobb méretű modellek irányában. Kutatásunkban különböző nagy méretű nyelvmodelleket tanítottunk magyar nyelvre. Betanítottunk egy 6,7 milliárd paraméteres GPT-3, valamint egy GPT-2 és egy BERT-Large modellt magyar nyelvre. A modelleket különböző finomhangolással teszteltük. A BERT-Large modellünk több feladatban is felülmúlta a huBERT modellt, és elsőként hoztunk létre egynyelvű magyar GPT-3 modellt, amelyekkel tudomásunk szerint elsőnek végeztünk prompt kísérleteket few-shot tanulással magyar nyelvre

A többnyelvű Európa újraformálása: A nyelvközpontú mesterséges intelligencia

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Multilingual comparable corpora of parliamentary debates ParlaMint 3.0

ParlaMint 3.0 is a multilingual set of 26 comparable corpora containing parliamentary debates mostly starting in 2015 and extending to mid-2022, with the individual corpora being between 9 and 125 million words in size. The corpora have extensive metadata, including aspects of the parliament; the speakers (name, gender, MP status, party affiliation, party coalition/opposition); are structured into time-stamped terms, sessions and meetings; and with speeches being marked by the speaker and their role (e.g. chair, regular speaker). The speeches also contain marked-up transcriber comments, such as gaps in the transcription, interruptions, applause, etc. Note that some corpora have further information, e.g. the year of birth of the speakers, links to their Wikipedia articles, their membership in various committees, etc. The corpora are also marked to the subcorpus they belong to ("reference", until 2020-01-30, "covid", from 2020-01-31, and "war", from 2022-02-24). The corpora are encoded according to the Parla-CLARIN TEI recommendation (https://clarin-eric.github.io/parla-clarin/), but have been encoded against the compatible, but much stricter ParlaMint encoding guidelines (https://clarin-eric.github.io/ParlaMint/) and schemas (included in this distribution. This entry contains the ParlaMint TEI-encoded corpora with the derived plain text versions of the corpora along with TSV metadata of the speeches. Also included is the 3.0 release of the data and scripts available at the GitHub repository of the ParlaMint project. Note that there also exists the linguistically marked-up version of the corpus, which is available at http://hdl.handle.net/11356/1488. As opposed to the previous version 2.1, this version extends the corpus dates to (at least) mid 2022, does not contain the corpora for ES (Spanish) and Lithuanian (LT), and adds corpora for AT (Austria), BA (Bosnian), ES-CT (Catalonia), ES-GA (Galicia), GR (Greece), NO (Norway), PT (Portugal), RS (Serbia), SE (Sweden), and UA (Ukraine). The TEI encoding of some details has also changed

Linguistically annotated multilingual comparable corpora of parliamentary debates in English ParlaMint-en.ana 3.0

ParlaMint-en 3.0 comprises linguistically annotated multilingual comparable corpora of parliamentary debates ParlaMint.ana 3.0 (http://hdl.handle.net/11356/1488) which were machine translated to English and the translation linguistically annotated. Except for the translation to English, small changes in the metadata and the absence of the British parliament corpus, the corpora included in this entry are all respects identical to the source language corpora, i.e. the entry comprises the same 26 European parliamentary corpora, together with over 1.1 billion words. The translation to English was done with EasyNMT (https://github.com/UKPLab/EasyNMT) with OPUS-MT models (https://github.com/Helsinki-NLP/Opus-MT). Machine translation was done on the sentence level, and includes both speeches and transcriber notes, including headings. The linguistic annotation of the speeches, i.e. tokenisation, tagging with UD PoS and morphological features, lemmatisation, and NER annotation was done with Stanza (https://stanfordnlp.github.io/stanza/), using the English language model. For NER the conll03 model with 4 NE classes was used. Note that the automatically produced translation to English contains errors typical of neural machine translation, which also includes factual errors even when a high level of fluency is achieved, and any manual or automatic usage of this corpus should take the machine translation limitations into account. Note also that some metadata errors were noticed after the source 3.0 corpora were released, and were corrected for the MTed corpus, so there are slight differences in the metadata between the two. The files associated with this entry include the linguistically annotated corpora in several formats: the corpora in thje canonical ParlaMint TEI XML encoding; the corpora in the derived vertical format (for use with CQP-based concordancers, such as CWB, noSketch Engine or KonText); and the corproa in the CoNLL-U format with TSV speech metadata. In contrast to the source language corpora, the CoNLL-U files are not derived from the TEI encoded corpus but are the ones output by the machine translation and linguistic annotation pipeline as these also contain word-alignment information, which is not present in the TEI version. Also included is the ParlaMint-en-3.0 release of the scripts and samples available at the GitHub repository of the ParlaMint project

Linguistically annotated multilingual comparable corpora of parliamentary debates ParlaMint.ana 3.0

ParlaMint 3.0 is a multilingual set of 26 comparable corpora containing parliamentary debates mostly starting in 2015 and extending to mid-2022, with the individual corpora being between 9 and 125 million words in size. The corpora have extensive metadata, including aspects of the parliament; the speakers (name, gender, MP status, party affiliation, party coalition/opposition); are structured into time-stamped terms, sessions and meetings; and with speeches being marked by the speaker and their role (e.g. chair, regular speaker). The speeches also contain marked-up transcriber comments, such as gaps in the transcription, interruptions, applause, etc. Note that some corpora have further information, e.g. the year of birth of the speakers, links to their Wikipedia articles, their membership in various committees, etc. The corpora are also marked to the subcorpus they belong to ("reference", until 2020-01-30, "covid", from 2020-01-31, and "war", from 2022-02-24). This entry contains the linguistically marked-up version of the corpus, while the text version is available at http://hdl.handle.net/11356/1486. The ParlaMint.ana linguistic annotation includes tokenization, sentence segmentation, lemmatisation, Universal Dependencies part-of-speech, morphological features, and syntactic dependencies, and the 4-class CoNLL-2003 named entities. Some corpora also have further linguistic annotations, such as PoS tagging or named entities according to language-specific schemes, with their corpus TEI headers giving further details on the annotation vocabularies and tools. The compressed files include the ParlaMint.ana XML TEI-encoded linguistically annotated corpus; the derived corpus in CoNLL-U with TSV speech metadata; and the vertical files (with registry file), suitable for use with CQP-based concordancers, such as CWB, noSketch Engine or KonText. Also included is the 3.0 release of the data and scripts available at the GitHub repository of the ParlaMint project. As opposed to the previous version 2.1, this version corrects some errors in various corpora and adds the information on upper / lower house for bicameral parliaments. The vertical files have also been changed to make them easier to use in the concordancers

Multilingual comparable corpora of parliamentary debates ParlaMint 4.0

ParlaMint 4.0 is a set of comparable corpora containing transcriptions of parliamentary debates of 29 European countries and autonomous regions, mostly starting in 2015 and extending to mid-2022. The individual corpora comprise between 9 and 126 million words and the complete set contains over 1.1 billion words. The transcriptions are divided by days with information on the term, session and meeting, and contain speeches marked by the speaker and their role (e.g. chair, regular speaker). The speeches also contain marked-up transcriber comments, such as gaps in the transcription, interruptions, applause, etc. The corpora have extensive metadata, most importantly on speakers (name, gender, MP and minister status, party affiliation), the political parties and parliamentary groups (name, coalition/opposition status, Wikipedia-sourced left-to-right political orientation, and CHES variables, https://www.chesdata.eu/). Note that some corpora have further metadata, e.g. the year of birth of the speakers, links to their Wikipedia articles, their membership in various committees, etc. The transcriptions are also marked with the subcorpus they belong to ("reference", until 2020-01-30, "covid", from 2020-01-31, and "war", from 2022-02-24). The corpora are encoded according to the Parla-CLARIN TEI recommendation (https://clarin-eric.github.io/parla-clarin/), but have been encoded against the compatible, but much stricter ParlaMint encoding guidelines (https://clarin-eric.github.io/ParlaMint/) and schemas (included in the distribution). This entry contains the ParlaMint TEI-encoded corpora and their derived plain text versions along with TSV metadata of the speeches. Also included is the 4.0 release of the sample data and scripts available at the GitHub repository of the ParlaMint project at https://github.com/clarin-eric/ParlaMint. Note that there also exists the linguistically marked-up version of the 4.0 ParlaMint corpus, also linked with concordancers, which is available at http://hdl.handle.net/11356/1860. As opposed to the previous version 3.0, this version adds corpora for Spain (ES), Finland (FI) and the Basque Country (ES-PV); extends the corpora for Austria (AT), Czechia (CZ), Hungary (HU), and Ukraine (UA) with more recent data; adds metadata to political parties and parliamentary groups on left-to-right political orientation from Wikipedia as well as CHES variables; and adds the information on whether a speaker was a minister and when for the corpora that previously lacked this information. The TEI encoding of some details has also changed, and many errors found in 3.0 corpora have been corrected