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opencc-zeroAug 2015View details →

Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages

Data and supplementary information for the paper entitled "Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages" to be published at EMNLP 2015: Conference on Empirical Methods in Natural Language Processing — September 17–21, 2015 — Lisboa, Portugal. ABSTRACT: Previous studies have shown that health reports in social media, such as DailyStrength and Twitter, have potential for monitoring health conditions (e.g. adverse drug reactions, infectious diseases) in particular communities. However, in order for a machine to understand and make inferences on these health conditions, the ability to recognise when laymen's terms refer to a particular medical concept (i.e. text normalisation) is required. To achieve this, we propose to adapt an existing phrase-based machine translation (MT) technique and a vector representation of words to map between a social media phrase and a medical concept. We evaluate our proposed approach using a collection of phrases from tweets related to adverse drug reactions. Our experimental results show that the combination of a phrase-based MT technique and the similarity between word vector representations outperforms the baselines that apply only either of them by up to 55%.

opencc-by-nc-sa-4.0Nov 2016View details →

Turkish Makam Symbolic Phrase Segmentation Dataset

makam-symbolic-phrase-segmentation-dataset Data sets containing pieces in SymbTr2 format segmented into phrases This study presents a large machine-readable dataset of Turkish makam music scores segmented into phrases by experts of this music. The segmentation facilitates computational research on melodic similarity between phrases, and relation between melodic phrasing and meter, rarely studied topics due to unavailability of data resources. It consists of 31362 phrases on a set of 480 scores of different compositions annotated by 3 experts. Please refer to the following publication if you use this data in your research: <blockquote> M. K. Karaosmanoglu, B. Bozkurt, A. Holzapfel, N. D. Disiacik, A symbolic dataset of Turkish makam music phrases, Folk Music Analysis Workshop (FMA), Istanbul, 2014. </blockquote> The refactored code for automatic phrase segmentation can be found here. For other deliverables of the paper please visit: http://www.rhythmos.org/shareddata/turkishphrases.html

opencc-by-4.0Feb 2022View details →

Based and confused: Tracing the political connotations of a memetic phrase across the web

opencc-by-4.0Jul 2015View details →

C-PHRASE Vectors

The C-PHRASE semantic vectors described in the following paper: N.T. Pham, G. Kruszewski, A. Lazaridou, M. Baroni <a href="https://www.aclweb.org/anthology/P15-1094">Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model.</a> Proceedings of ACL 2015 (53rd Annual Meeting of the Association for Computational Linguistics). The vectors are the rows of a dense matrix stored in a text file using the tab-delimited format (the first element of each line corresponds to a word, followed by the values in the vector representing it). The text file is then compressed and split it into two files to make the download easier. Please download the following parts, and then concatenate them as shown below: <ul> <li>cphrase.txt.zip_aa</li> <li>cphrase.txt.zip_ab</li> </ul> <code>cat cphrase.txt.zip_* > cphrase.txt.zip</code>

opencc-by-4.0May 2018View details →

Abstractions and exemplars: the measure noun phrase alternation in German

This is the data set and scripts used in "Abstractions and exemplars: the measure noun phrase alternation in German" as accepted for publication in Cognitive Linguistics as of 29 may 2018. In this paper, an alternation in German measure noun phrases is examined under a varying-abstraction perspective. In a specific measure NP construction, the embedded kind-denoting noun either agrees in case with the measure noun ("eine Tasse guter Kaffee" 'a cup of good coffee') or it stands in the genitive ("eine Tasse guten Kaffees"). Each of the two alternants is syntactically similar to a non-alternating construction. I propose a prototype model which assigns a common prototypical meaning to each of the alternants and its corresponding non-alternating construction. Based on this, I argue that lexical, morpho-syntactic, and stylistic features help to predict the choice of the alternant. A large corpus study is presented which supports this analysis. However, in addition to the prototype effects, an exemplar effect is also shown to influence the choice, namely the relative frequencies with which lemmas occur in the non-alternating constructions. I argue that allowing both prototype and exemplar effects is more adequate than following radical prototype or exemplar approaches. It is also verified in two experiments that the corpus-derived model corresponds to the behaviour of native speakers. The weak effect size of the experimental validation is discussed in the context of corpus-based cognitive linguistics and the validation of corpus-derived models.

opencc-by-4.0Jan 2019View details →

BenchPS: A Benchmark Dataset for Phrase Simplification

BenchPS is a dataset built for the training and evaluation of phrase simplification systems. Each instance is composed of a sentence, target complex phrase, and a set of candidate simplifications ranked by simplicity. Each instance was annotated by humans through multiple annotations steps to ensure the reliability of the data.

opencc-by-4.0May 2023View details →

Supplementary material for "Using a parallel corpus to study patterns of word order variation: Determiners and quantifiers within the noun phrase in European languages"

- output-{ciep,treebanks}-full.csv: frequency and entropy for all the categories, using four types of combinations of layers; - plots.R: R script to draw plots from the output files; - readReport-{CIEP+,treebanks}.R: R script to extract frequency and compute entropy from the report files (not included); - ud-wordorder.py: Python script to extract word order pairs from conllu files and write them in report files. Unfortunately, I cannot include the report files, as CIEP+ is protected by copyright; the analysis can be however replicated with respect to the UD Treebanks.

opencc-by-4.0May 2023View details →

Video no. 1 'Motif, phrase in working on music choreography' by Barbara Dutkiewicz

The footage complements the publication by Barbara Dutkiewicz (2023) &sbquo;Choreography of music. Process of creation according to the principles of plastique animée on the example of music by Henryk Mikołaj Górecki 'Kleines Requiem für eine Polka op. 66’, choreography created by Barbara Dutkiewicz and Iga Eckert’ (DOI: <a href="https://doi.org/10.5281/zenodo.7789711">https://doi.org/10.5281/zenodo.7789711</a>), written as a part of the intellectual output of the project EURHYTHMICS IN EDUCATION AND ARTISTIC PRACTICE (ERASMUS+). implemented in 2020-2023. Workshop with students of The Karol Szymanowski Academy of Music in Katowice, Poland and Universität für Musik und darstellende Kunst Wien, Austria took place during LTT, host Katowice 21-25.03.2022. Artistic direction: Associate Professor Barbara Dutkiewicz (PhD.hab) and Iga Eckert, MA. ISBN  978-83-963687-3-7 The article is supplemented by photos and four videos: - Video no. 1  ’Motif, phrase in working on music choreography’ by Barbara Dutkiewicz <a href="https://doi.org/10.5281/zenodo.7922029">https://doi.org/10.5281/zenodo.7922029</a> - Video no 2. ’Exercises with polymetric structure in working on music choreography’ by Iga Eckert and Barbara Dutkiewicz <a href="https://doi.org/10.5281/zenodo.7916295">https://doi.org/10.5281/zenodo.7916295</a>  - Video no. 3 ’Movement stylization and multi planarity in working on music choreography’ by Barbara Dutkiewicz <a href="https://doi.org/10.5281/zenodo.7922104">https://doi.org/10.5281/zenodo.7922104</a> - Video no. 4  'A short exercise on body awareness - movement technique in working on music choreography’ by Barbara Dutkiewicz <a href="https://doi.org/10.5281/zenodo.7916598">https://doi.org/10.5281/zenodo.7916598</a> This article and videos are published on the digital platform "Atlas of Eurhythmics"  <a href="https://www.kmh.se/in-english/atlas-of-eurhythmics/results-from-the-project.html">https://www.kmh.se/in-english/atlas-of-eurhythmics/results-from-the-project.html</a>  at modul: "Plastique animée - tradition and contemporary performing".

opencc-by-4.0Jan 2022View details →

Armenian: Noun phrase structure and determination

<ul> <li> Basic word order in noun phrase </li> <li> Basic characteristics of definite article </li> <li> Parallels between noun phrase and clause </li> <li> Definite article and specificity </li> <li> Definite article and nominalization </li> <li> Definite article as marker of argumenthood </li> <li> Typological parallels </li> </ul>   This lecture is part of the lecture series: Glottothèque: Languages of the Anatolia, Caucasus, Iran, Mesopotamia; grammatical snippets online (electronic resource). Bamberg, Cambridge, Göttingen, Moskow, Nicosia, Paris: LACIM network, at https://spw.uni-goettingen.de/projects/lacim/, edited by Christiane Bulut, Anaïd Donabédian-Demopoulos, Geoffrey Haig, Geoffrey Khan, Pollet Samvelian, Stavros Skopeteas, Nina Sumbatova.

opencc-by-nc-nd-4.0Sep 2014View details →

Turkish Makam Melodic Phrase Dataset

Karaosmanoğlu and Bozkurt have studied the problem of usul and makam driven automatic melodic segmentation for Turkish Music. There are 899 SymbTr-scores. The scores were manually annotated into melodic segments by 3 experts. In total, there are 31362 phrase annotations in this dataset. Using this dataset Please refer to the following paper if you use the SymbTr data: <blockquote> B. Bozkurt, M. K. Karaosmanoğlu, B. Karaçalı, and E. Ünal. 2014. Usul and Makam Driven Automatic Melodic Segmentation for Turkish Music. Journal of New Music Research, 43:4, pp. 375-389. </blockquote> <a href="https://doi.org/10.1080/09298215.2014.924535">https://doi.org/10.1080/09298215.2014.924535</a> Please refer to the following paper if you use the Matlab code: <blockquote> M. K. Karaosmanoglu, B. Bozkurt, A. Holzapfel, N. D. Disiacik, A symbolic dataset of Turkish makam music phrases, Folk Music Analysis Workshop (FMA), Istanbul, 2014. </blockquote> We are interested in knowing if you find our datasets useful! If you use our dataset please email us at <a href="mailto:mtg-info@upf.edu">mtg-info@upf.edu</a> and tell us about your research.   <a href="http://compmusic.upf.edu/node/236">http://compmusic.upf.edu/node/236</a>

opencc-by-4.0Jun 2021View details →

Tortured phrases: A dubious writing style emerging in science. Evidence of critical issues affecting established journals.

Supplementary materials to preprint <a href="https://arxiv.org/abs/2107.06751">https://arxiv.org/abs/2107.06751</a>.

opencc-by-4.0Jan 2023View details →

Silver Standard of quantified positive, negative and neutral German noun phrases

Repository: silver standard quantified (simple) noun phrases 43,842 positive (+), negative (-) or neutral (0) NPs,  e.g. "ein notorischer Verführer    -5.625" is highly negative (-5.625) see References LREC for a description of the data Format: tsv References: @inproceedings{LREC,            month = {Juni},           author = {Manfred Klenner and Anne G{\"o}hring},        booktitle = {Proceedings of the Language Resources and Evaluation Conference},          address = {Marseille, France},            title = {Animacy Denoting {G}erman Nouns: Annotation and Classification},        publisher = {European Language Resources Association},            pages = {1360--1364},             year = {2022},         language = {english},              url = {https://doi.org/10.5167/uzh-219148},         abstract = {In this paper, we introduce a gold standard for animacy detection comprising almost 14,500 German nouns that might be used to denote either animate entities or non-animate entities. We present inter-annotator agreement of our crowd-sourced seed annotations (9,000 nouns) and discuss the results of machine learning models applied to this data.} }

opencc-by-4.0May 2020View details →

Une base de données de phrases en français pour l'étude du rôle conjoint des incertitudes sémantique et acoustique dans la perception de la parole.

Une base de données de phrases présentant des caractéristiques de lien sémantique varié avec des mots-cible monosyllabiques. Ces phrases ont été conçues à partir de mesures de plongements de mots issues d'un modèle du corpus Wikipedia en français.

opencc-by-4.0May 2020View details →

Breaking the Mold: A corpus study of numeral+noun phrases in Scottish Gaelic - Corpus Data

Hello! This is the corpus data compiled in the searches done for my master's thesis: Breaking the Mold: A corpus study of numeral + noun phrases in Scottish Gaelic. The data comes from the Digital Archive of Scottish Gaelic's Corpas na Gàidhlig (<a href="https://dasg.ac.uk/corpus/">https://dasg.ac.uk/corpus/</a>).  The relevant data are discussed in the thesis, but the full corpus is found here for anyone who wishes to view it.  For any questions, please contact me: emma.mckenzie(at)helsinki.fi

opencc-zeroJan 2015View details →

Phrase-Level Word Embeddings

Phrase-level word embeddings for sentiment analysis.

opencc-by-4.0May 2022View details →

Supplementary material for "Tweaking UD annotations to investigate the placement of determiners, quantifiers and numerals in the noun phrase"

The supplementary material includes <ul> <li>the Python script used to extract relevant word order patterns from the parsed corpus;</li> <li>the R script used to process the extracted data, also containing the list of lemmata;</li> <li>a spreadsheet featuring the frequency and entropy values.</li> <li>a doc file with comparative concepts for the investigated categories.</li> </ul>

opencc-by-4.0May 2022View details →

Neural dynamics differentially encode phrases and sentences in spoken language comprehension

Data used to plot the summarized figures in the research article, Neural dynamics differentially encode phrases and sentences in spoken language comprehension.