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A "Wind of Change" Shaping public opinion of the "Arab Spring" using metaphors
Núñez, Alexandra; Gerloff, Malte; Do Dinh, Erik-Lan; Rapp, Andrea; Gehring, Petra; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Alliance of Digital Humanities (Hrsg.): Digital Humanities 2017: Conference abstracts, McGill University & Université de Montréal, Montréal, Canada, August 8.11, 2017 | Montréal: Alliance of Digital Humanities | 2017
37342 Endnote
Autor*innen:
Núñez, Alexandra; Gerloff, Malte; Do Dinh, Erik-Lan; Rapp, Andrea; Gehring, Petra; Gurevych, Iryna
Titel:
A "Wind of Change" Shaping public opinion of the "Arab Spring" using metaphors
Aus:
Alliance of Digital Humanities (Hrsg.): Digital Humanities 2017: Conference abstracts, McGill University & Université de Montréal, Montréal, Canada, August 8.11, 2017, Montréal: Alliance of Digital Humanities, 2017 , S. 551-553
URL:
https://dh2017.adho.org/abstracts/041/041.pdf
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Automatisierung; Computerlinguistik; Einflussfaktor; Grammatik; Metapher; Öffentliche Meinung; Presseberichterstattung; Semantik; Textanalyse
Abstract:
How does mass media affect the way we think about controversial topics such as the "Arab Spring"? What persuasive role do metaphors play especially in opinion pieces? We analyze how the political events of the years 2010-2011 in the Middle East and North Africa Region ("Arab Spring") are categorized and assessed using metaphorical constructions in newspaper opinion pieces. We show ways in which particularly the use of metaphors reveals how the media tried to achieve acceptance for the events based on our cultural models (Quinn and Holland, 1987), which are grounded on our western knowledge. To this end, we constructed a pipeline that automatically detects (and filters) metaphors appearing within certain grammatical constructions, before clustering them by presumed source and target domains (Conceptual Metaphor Theory, Lakoff and Johnson, 1980). The results give us insights into how the "Arab Spring" is metaphorically structured by semantic clusters in opinion pieces. (DIPF/Autor)
DIPF-Abteilung:
Informationszentrum Bildung
Reporting score distributions makes a difference. Performance study of LSTM-networks for sequence […]
Reimers, Nils; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Association for Computational Linguistics (Hrsg.): The Conference on Empirical Methods in Natural Language Processing (EMNLP 2017): Proceedings of the Conference, September 9-11, 2017, Copenhagen, Denmark | Stroudsburg; PA: Association for Computational Linguistics | 2017
37871 Endnote
Autor*innen:
Reimers, Nils; Gurevych, Iryna
Titel:
Reporting score distributions makes a difference. Performance study of LSTM-networks for sequence tagging
Aus:
Association for Computational Linguistics (Hrsg.): The Conference on Empirical Methods in Natural Language Processing (EMNLP 2017): Proceedings of the Conference, September 9-11, 2017, Copenhagen, Denmark, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 338-348
URL:
http://www.aclweb.org/anthology/D/D17/D17-1035.pdf
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Computerlinguistik; Spracherkennung
Abstract:
In this paper we show that reporting a single performance score is insufficient to compare non-deterministic approaches. We demonstrate for common sequence tagging tasks that the seed value for the random number generator can result in statistically significant (p < 10^-4) differences for state-of-the-art systems. For two recent systems for NER, we observe an absolute difference of one percentage point F1-score depending on the selected seed value, making these systems perceived either as state-of-the-art or mediocre. Instead of publishing and reporting single performance scores, we propose to compare score distributions based on multiple executions. Based on the evaluation of 50.000 LSTM-networks for five sequence tagging tasks, we present network architectures that produce both superior performance as well as are more stable with respect to the remaining hyperparameters. The full experimental results are published in (Reimers and Gurevych, 2017). The implementation of our network is publicly available. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
End-to-end non-factoid question answering with an interactive visualization of neural attention […]
Rücklé, Andreas; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Association for Computational Linguistics (Hrsg.): Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, July 30 - August 4, 2017: System demonstrations | Stroudsburg; PA: Association for Computational Linguistics | 2017
37876 Endnote
Autor*innen:
Rücklé, Andreas; Gurevych, Iryna
Titel:
End-to-end non-factoid question answering with an interactive visualization of neural attention weights
Aus:
Association for Computational Linguistics (Hrsg.): Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, July 30 - August 4, 2017: System demonstrations, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 19-24
DOI:
10.18653/v1/P17-4004
URL:
https://aclanthology.info/pdf/P/P17/P17-4004.pdf
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Computerlinguistik; Aufmerksamkeit; Vernetzung; Modell; Struktur; Analyse; Visualisierung; Forschung; Frage; Antwort; Benutzeroberfläche
Abstract:
Advanced attention mechanisms are an important part of sucessful neural network approaches for non-factoid answer selection because they allow the models to focus on few important segments within rather long answer texts. Analyzing attention mechanisms is thus crucial for understanding strengths and weaknesses of particular models. We present an extensible, highly modular service architecture that enables the transformation of neural network models for non-factoid answer selection into fully featured end-to-end question answering systems. The primary objective of our system is to enable researchers a way to interactively explore and compare attention-based neural networks for answer selection. Our interactive user interface helps researchers to better understand the capabilities of the different approaches and can aid qualitative analyses. The source-code of our system is publicly available. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Training argumentation skills with argumentative writing support
Stab, Christian; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Petukhova, Volha; Tian, Ye (Hrsg.): Proceedings of the 21st Workshop on the Semantics and Pragmatics Dialogue (SEMDIAL 2017 SaarDial), Saarbrücken, 15-17 August 2017 | Saarbrücken: Saarland Universität | 2017
37873 Endnote
Autor*innen:
Stab, Christian; Gurevych, Iryna
Titel:
Training argumentation skills with argumentative writing support
Aus:
Petukhova, Volha; Tian, Ye (Hrsg.): Proceedings of the 21st Workshop on the Semantics and Pragmatics Dialogue (SEMDIAL 2017 SaarDial), Saarbrücken, 15-17 August 2017, Saarbrücken: Saarland Universität, 2017 (Proceedings (SemDial)), S. 174-175
URL:
www.saardial.uni-saarland.de/wordpress/wp-content/uploads/SemDial2017SaarDial_proceedings.pdf#page=182
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Argumentation; Computerlinguistik; Textanalyse
Abstract:
We present an writing support system for assessing written arguments. Our system incorporates three analysis models allowing for rich feedback about argumentation structure, quality of reasons, and presence of opposing arguments. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Integrating deep linguistics features in factuality prediction over unified datasets
Stanovsky, Gabriel; Eckle-Kohler, Judith; Puzikov, Yevgeniy; Dagan, Ido; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Association for Computational Linguistics (Hrsg.): The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017): Proceedings of the conference, vol. 2 (short papers), July 30 - August 4, 2017, Vancouver, Canada | Stroudsburg; PA: Association for Computational Linguistics | 2017
37874 Endnote
Autor*innen:
Stanovsky, Gabriel; Eckle-Kohler, Judith; Puzikov, Yevgeniy; Dagan, Ido; Gurevych, Iryna
Titel:
Integrating deep linguistics features in factuality prediction over unified datasets
Aus:
Association for Computational Linguistics (Hrsg.): The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017): Proceedings of the conference, vol. 2 (short papers), July 30 - August 4, 2017, Vancouver, Canada, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 352-357
DOI:
10.18653/v1/P17-2056
URL:
https://aclanthology.info/pdf/P/P17/P17-2056.pdf
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Computerlinguistik; Modell; Methode; Daten; Sprache; Wort; Semantik
Abstract:
Previous models for the assessment of commitment towards a predicate in a sentence (also known as factuality prediction) were trained and tested against a specific annotated dataset, subsequently limiting the generality of their results. In this work we propose an intuitive method for mapping three previously annotated corpora onto a single factuality scale, thereby enabling models to be tested across these corpora. In addition, we design a novel model for factuality prediction by first extending a previous rule-based factuality prediction system and applying it over an abstraction of dependency trees, and then using the output of this system in a supervised classifier. We show that this model outperforms previous methods on all three datasets. We make both the unified factuality corpus and our new model publicly available. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Argumentation quality assessment. Theory vs. practice
Wachsmuth, Henning; Naderi, Nona; Habernal, Ivan; Hou, Yufang; Hirst, Graeme; Gurevych, Iryna; […]
Sammelbandbeitrag
| Aus: Association for Computational Linguistics (Hrsg.): The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017): Proceedings of the conference, vol. 2 (short papers), July 30 - August 4, 2017. Vancouver, Canada | Stroudsburg; PA: Association for Computational Linguistics | 2017
37875 Endnote
Autor*innen:
Wachsmuth, Henning; Naderi, Nona; Habernal, Ivan; Hou, Yufang; Hirst, Graeme; Gurevych, Iryna; Stein, Benno
Titel:
Argumentation quality assessment. Theory vs. practice
Aus:
Association for Computational Linguistics (Hrsg.): The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017): Proceedings of the conference, vol. 2 (short papers), July 30 - August 4, 2017. Vancouver, Canada, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 250-255
DOI:
10.18653/v1/P17-2039
URL:
https://aclanthology.info/pdf/P/P17/P17-2039.pdf
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Computerlinguistik; Argumentation; Diskussion; Qualität; Bewertung; Theorie; Praxis; Vergleich
Abstract:
Argumentation quality is viewed differently in argumentation theory and in practical assessment approaches. This paper studies to what extent the views match empirically. We find that most observations on quality phrased spontaneously are in fact adequately represented by theory. Even more, relative comparisons of arguments in practice correlate with absolute quality ratings based on theory. Our results clarify how the two views can learn from each other. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Generating training data for semantic role labeling based on label transfer from linked lexical […]
Hartmann, Silvana; Eckle-Kohler, Judith; Gurevych, Iryna
Zeitschriftenbeitrag
| In: Transactions of the Association for Computational Linguistics | 2016
36232 Endnote
Autor*innen:
Hartmann, Silvana; Eckle-Kohler, Judith; Gurevych, Iryna
Titel:
Generating training data for semantic role labeling based on label transfer from linked lexical resources
In:
Transactions of the Association for Computational Linguistics, (2016)
URL:
https://tacl2013.cs.columbia.edu/ojs/index.php/tacl/article/view/717
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Schlagwörter:
Ambiguität; Automatisierung; Computerlinguistik; Computerunterstütztes Verfahren; Semantik; Textanalyse; Wort; Wörterbuch
Abstract (english):
We present a new approach for generating role-labeled training data using Linked Lexical Resources, i.e., integrated lexical resources that combine several resources (e.g., WordNet, FrameNet, Wiktionary) by linking them on the sense or on the role level. Unlike resource-based supervision in relation extraction, we focus on complex linguistic annotations, more specifically FrameNet senses and roles. The automatically labeled training data (http://www.ukp.tu-darmstadt.de/knowledge-based-srl/) are evaluated on four corpora from different domains for the tasks of word sense disambiguation and semantic role classification. Results show that classifiers trained on our generated data equal those resulting from a standard supervised setting. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Automatic coding of short text responses via clustering in educational assessment
Zehner, Fabian; Sälzer, Christine; Goldhammer, Frank
Zeitschriftenbeitrag
| In: Educational and Psychological Measurement | 2016
35473 Endnote
Autor*innen:
Zehner, Fabian; Sälzer, Christine; Goldhammer, Frank
Titel:
Automatic coding of short text responses via clustering in educational assessment
In:
Educational and Psychological Measurement, 76 (2016) 2, S. 280-303
DOI:
10.1177/0013164415590022
URN:
urn:nbn:de:0111-pedocs-149795
URL:
https://nbn-resolving.org/urn:nbn:de:0111-pedocs-149795
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Schlagwörter:
Antwort; Automatisierung; Codierung; Computerlinguistik; Leistungstest; Methode; PISA <Programme for International Student Assessment>; Software; Technologiebasiertes Testen; Testkonstruktion
Abstract:
Automatic coding of short text responses opens new doors in assessment. We implemented and integrated baseline methods of natural language processing and statistical modelling by means of software components that are available under open licenses. The accuracy of automatic text coding is demonstrated by using data collected in the Programme for International Student Assessment (PISA) 2012 in Germany. Free text responses of 10 items with Formula responses in total were analyzed. We further examined the effect of different methods, parameter values, and sample sizes on performance of the implemented system. The system reached fair to good up to excellent agreement with human codings Formula Especially items that are solved by naming specific semantic concepts appeared properly coded. The system performed equally well with Formula and somewhat poorer but still acceptable down to Formula Based on our findings, we discuss potential innovations for assessment that are enabled by automatic coding of short text responses. (DIPF/Orig.)
DIPF-Abteilung:
Bildungsqualität und Evaluation
Argumentation. Content, structure, and relationship with essay quality
Beigman Klebanov, Beata; Stab, Christian; Song, Yi; Gyawali, Binod; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Association for Computational Linguistics (Hrsg.): Proceedings of the 3rd Workshop on Argument Mining held in conjunction with the 2016 Annual Meeting of the Association for Computational Linguistics (ACL 2016) | Stroudsburg; PA: Association for Computational Linguistics | 2016
36977 Endnote
Autor*innen:
Beigman Klebanov, Beata; Stab, Christian; Song, Yi; Gyawali, Binod; Gurevych, Iryna
Titel:
Argumentation. Content, structure, and relationship with essay quality
Aus:
Association for Computational Linguistics (Hrsg.): Proceedings of the 3rd Workshop on Argument Mining held in conjunction with the 2016 Annual Meeting of the Association for Computational Linguistics (ACL 2016), Stroudsburg; PA: Association for Computational Linguistics, 2016 , S. 70-75
URL:
http://aclweb.org/anthology/W/W16/W16-2808.pdf
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Argumentation; Aufsatz; Computerlinguistik; Evaluation; Experiment; Inhalt; Qualität; Struktur
Abstract (english):
In this paper, we investigate the relationship between argumentation structures and (a) argument content, and (b) the holistic quality of an argumentative essay. Our results suggest that structure-based approaches hold promise for automated evaluation of argumentative writing. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Supersense embeddings. A unified model for supersense interpretation, prediction and utilization
Flekova, Lucie; Gurevych, Iryna
Sammelbandbeitrag
| Aus: Association for Computational Linguistics (Hrsg.): Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016): Long Papers | Stroudsburg; PA: Association for Computational Linguistics | 2016
36971 Endnote
Autor*innen:
Flekova, Lucie; Gurevych, Iryna
Titel:
Supersense embeddings. A unified model for supersense interpretation, prediction and utilization
Aus:
Association for Computational Linguistics (Hrsg.): Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016): Long Papers, Stroudsburg; PA: Association for Computational Linguistics, 2016 , S. 2029-2041
URL:
http://www.aclweb.org/anthology/P16-1191
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Schlagwörter:
Beziehung; Computerlinguistik; Klassifikation; Semantik; Sinn; Wort
Abstract (english):
Coarse-grained semantic categories such as supersenses have proven useful for a range of downstream tasks such as question answering or machine translation. To date, no effort has been put into integrating the supersenses into distributional word representations. We present a novel joint embedding model of words and supersenses, providing insights into the relationship between words and supersenses in the same vector space. Using these embeddings in a deep neural network model, we demonstrate that the supersense enrichment leads to a significant improvement in a range of downstream classification tasks. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
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