2026-10-12T12:52:28Z https://fdat.uni-tuebingen.de/oai2d

oai:fdat.uni-tuebingen.de:902tc-h3843 2026-06-15T16:47:47Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:902tc-h3843 Linguistic Data Consortium University of Tübingen 2012 linguistics 2012-11-21 2026-06-15 10.57754/FDAT.902tc-h3843 https://catalog.ldc.upenn.edu/LDC95T21 https://fdat.uni-tuebingen.de/communities/crc833/ Linguistic Data Consortium, The Trustees of the University of Pennsylvania. The corpus is composed of news text that has been formatted using TIPSTER-style SGML markup.

oai:fdat.uni-tuebingen.de:p64a7-6qh34 2026-06-15T16:47:48Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:p64a7-6qh34 Maienborn, Claudia Claudia Maienborn gnd:179660357 University of Tübingen University of Tübingen 2016 linguistics 2016-04-12 2026-06-15 10.57754/FDAT.p64a7-6qh34 https://fdat.uni-tuebingen.de/communities/crc833/ Restricted. Diese Studie diente dazu, das Material für eine geplante Augenbewegungsstudie zu testen.   Teilnehmer 7 Mitarbeiter der Universität Tübingen.   Material Die Studie hatte einen 2x2 Design mit Faktoren VERBTYP (atelisch und telisch) und DIREKTIONALPHRASE (telisch und ambig). 8 Bewegungsverbpaaren wurden jeweils 4 Mal mit unterschiedlichen Satzmaterial verwendet. Die Sätze hatten die folgende Struktur: definiter Subjekt + Verb + Direktionalphrase. 32 Items und 64 Fillers wurden nach dem lateinischen Quadrat auf vier pseudorandomisierte Listen verteilt, sodass keine zwei gleiche Verben oder Bedingungen nacheinander kamen. Die Filler hatten eine ähnliche Struktur zu den Items, aber andere Verben. Die Fillers variierten in der Natürlichkeit aufgrund der Semantik.   Verfahren Das Experiment wurde mit der freien Software OnExp 1.2 programmiert. Die Aufgabe war, Sätze zu lesen und die Natürlichkeit dieser Sätze auf einer 5-Punkt Skala zu bewerten (1 sehr unnatürlich bis 5 sehr natürlich). Die Versuchsteilnehmer saßen an einem Rechner in einem Computer-Pool und haben den Fragebogen ca. 15 Minuten lang bearbeitet. Das Experiment wurde von drei Übungsdurchgängen eingeleitet. This study tested the material for a planed eye-tracking experiment.   Participants: 7 researchers from the University of Tübingen.   Material: The study had a 2x2 design with the factors verb type (atelic vs. telic) and directional phrase (ambiguous vs. telic). 16 motion verbs from the self-paced reading study were split into two groups based on their telicity score (see above). Atelic verbs were then paired with telic ones. In order to obtain a sufficient 25 number of items, the resulting eight pairs were used four times in different contexts. All sentences contained a definite subject, a verb, and a directional phrase (see (1)). 32 items in four conditions and 64 fillers were distributed over four lists in a Latin square design. The lists were pseudorandomised in two counterbalanced orders, so that no two conditions or items of the same type were in direct proximity. The fillers had a similar syntax to the items, but different verbs, noun 30 and prepositional phrases were used than in the items. The naturalness of the fillers was varied and the unnaturalness was caused by semantic mismatches.   Procedure: The experiment was programmed with the OnExp 1.2 software. The participants were seated in a computer pool and asked to rate the naturalness of the sentences on a 5-point Likert scale from 1 very unnatural to 5 very natural. The main experiment was preceded by three practice trials and each list began with three filler items. It took about 15 minutes on average to complete the experiment. Das Experiment wurde mit der freien Software OnExp 1.2 programmiert. Die Aufgabe war, Sätze zu lesen und die Natürlichkeit dieser Sätze auf einer 5-Punkt Skala zu bewerten (1 sehr unnatürlich bis 5 sehr natürlich). Die Versuchsteilnehmer saßen an ihren eigenen Rechnern und haben den Fragebogen bearbeitet. Das Experiment wurde von drei Übungsdurchgängen eingeleitet. Research carried out in work package A01 of the SFB 833. Deutsche Forschungsgemeinschaft 018mejw64 75650358 SFB 833:  Bedeutungskonstitution - Dynamik und Adaptivität sprachlicher Strukturen

oai:fdat.uni-tuebingen.de:8ejtn-z4p98 2026-06-15T16:47:49Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:8ejtn-z4p98 Schuster, Alexandra Alexandra Schuster 0000-0002-4093-8752 University of Tübingen University of Tübingen 2020 linguistics 2020-10-29 2026-06-15 10.57754/FDAT.8ejtn-z4p98 https://fdat.uni-tuebingen.de/communities/crc833/ Creative Commons Attribution Non Commercial No Derivatives 4.0 International This data set comprises data from a questionary combining different forms of studies, such as filling in gaps, chosing from given elements and writing a short text. In this study, participants described two short picture stories by E. O. Plauen (series "Vater und Sohn": Missglückte Herausforderung and Rauchringe). After that, they were given a sentence with two gaps to fill in, the verbs were given. The next gaps had to be filled with the prefered form by chosing between two given elements. The last three sentences described a given short picture story (Hoffnungsloser Fall) and participants had to fill the gaps with the prefered verb form by chosing between given elements. Research carried out in work package C07 of the SFB 833. Deutsche Forschungsgemeinschaft 018mejw64 75650358 SFB 833:  Bedeutungskonstitution - Dynamik und Adaptivität sprachlicher Strukturen

oai:fdat.uni-tuebingen.de:ghpmj-31657 2026-06-15T16:47:50Z community-faculty_science

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:ghpmj-31657 Madella, Andrea Andrea Madella 0000-0001-8987-6612 University of Tübingen Ehlers, Todd Todd Ehlers 0000-0001-9436-0303 University of Glasgow University of Tübingen 2021 geology geophysics geomorphology 2021-06-24 2021-05-25 2026-06-15 eng 10.57754/FDAT.ghpmj-31657 https://fdat.uni-tuebingen.de/communities/faculty_science/ Creative Commons Attribution 4.0 International This is a post-peer-review, pre-copyedit version of an article published in Nature Geoscience. The final authenticated version is available online at: https://doi.org/10.1038/s41561-021-00779-0. In addition to the manuscript and supplementary information, a csv file with the most relevant new data of the study is provided. The csv file contains the seismic catalog after the corrections explained in the methods and supplementary material sections (removal of seismic events based on Magnitude of completeness and dense earthquake clustering in space and time). the last 5 columns inform the following items. # slab_depth: depth of the subduction interface beneath the epicenter # lat_corr: corrected latitude, projected to the swath line in Fig. 1 of the main text # trench_d: horizontal distance to the trench line # DEPDIF: vertical distance (km) between the hypocenter and the subduction interface, positive when below the interface # MOM: seismic Moment (Nm) generated by the event. Swiss National Science Foundation 00yjd3n13 178460 Early Postdoc Mobility

oai:fdat.uni-tuebingen.de:gyq3b-cpy08 2026-06-15T16:47:50Z community-crc441

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:gyq3b-cpy08 Obrist, Philipp Philipp Obrist 0000-0002-6789-9466 University of Tübingen University of Tübingen 2008 linguistics 2008-03-15 2026-06-15 10.57754/FDAT.gyq3b-cpy08 https://fdat.uni-tuebingen.de/communities/crc441/ Restricted. Discourse Tradition of Romance Languages and multi-dimensional Corpus Analysis: Digitalized complete newspaper texts, taken from the Internet and annotated for sentence connectors. Research carried out in work package B14 of the SFB 441. Deutsche Forschungsgemeinschaft 018mejw64 5483349 SFB 441: Linguistische Datenstrukturen: Theoretische und empirische Grundlagen der Grammatikforschung

oai:fdat.uni-tuebingen.de:2p4w9-1wg41 2026-06-15T16:47:50Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:2p4w9-1wg41 De Kuthy, Kordula Kordula De Kuthy University of Tübingen Ziai, Ramon Ramon Ziai 0000-0003-0944-0590 University of Tübingen Meurers, Detmar Detmar Meurers gnd:172851750 University of Tübingen University of Tübingen 2020 linguistics 2020-11-11 2026-06-15 10.57754/FDAT.2p4w9-1wg41 http://www.lrec-conf.org/proceedings/lrec2016/pdf/1083_Paper.pdf https://fdat.uni-tuebingen.de/communities/crc833/ Creative Commons Attribution Non Commercial Share Alike 4.0 International CREG-ExpertFocus, expert focus annotation of question answer pairs. Two trained annotators manually performed focus annotation (4,177 question answer pairs of the CREG-5K corpus manually annotated with focus). Research carried out in work package A04 of the SFB 833. Deutsche Forschungsgemeinschaft 018mejw64 75650358 SFB 833:  Bedeutungskonstitution - Dynamik und Adaptivität sprachlicher Strukturen

oai:fdat.uni-tuebingen.de:0yjbq-rze07 2026-06-15T16:47:51Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:0yjbq-rze07 de Kok, Daniël Daniël de Kok University of Tübingen University of Tübingen 2019 linguistics 2019-05-01 2026-06-15 10.57754/FDAT.0yjbq-rze07 10.57754/FDAT.721tn-jef87 https://fdat.uni-tuebingen.de/communities/crc833/ Creative Commons Attribution Non Commercial No Derivatives 4.0 International  If you want to use this dataset for research purposes, please refer to the following sources:                  - Roland  Schäfer. 2015. Processing  and  querying large  web  corpora  with  the  COW14  architecture. In Proceedings of Challenges in the Management of Large Corpora 3 (CMLC-3),  Lancaster. UCREL, IDS.                  - Roland Schäfer and Felix Bildhauer. 2012. Building Large Corpora from the Web Using a New Efficient  Tool  Chain. In Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12),  pages 486–493, Istanbul, Turkey. European Language Resources Association (ELRA).                  - Corina Dima, Daniël de Kok, Neele Witte, Erhard Hinrichs. 2019. No word is an island — a transformation weighting model for semantic composition. Transactions of the Association for Computational Linguistics. The dataset is distributed under the Creative Commons Attribution NonCommercial (CC-BY-NC) license. This dataset contains 238,975 English adjective-noun phrases (split into 167,292 train, 47,803 test, 23,880 dev instances) that were automatically extracted from the ENCOW16AX treebank (Schäfer  and  Bildhauer, 2012;  Schäfer,  2015). The phrases were extracted with the help of the part-of-speech tag information provided by the treebank. The train/test/dev files have the following format, single parts separated by tab: adjective noun adj-noun phrase, where the adjective and the noun are separated by the string _adj_n_ (e.g. good networking good_adj_n_networking). For results of different composition models on this dataset see Dima et al. (2019) ), No word is an island — a transformation weighting model for semantic composition. The word embeddings were trained on ENCOW16AX, which contains crawled web data from different sources. The training corpus was filtered to only contain sentences with a document quality of a or b to avoid noisy data. To ensure that trained word embeddings for enough adjective-noun phrases are available, the embeddings were trained on word forms, instead of lemmas. The final training corpus for the word embeddings contains 89.0M sentences and 2.2B  tokens. The embeddings for the adjectives, nouns and phrases were trained jointly, with the word2vec package (Mikolov et al. 2013), using the skipgram model with negative sampling, a symmetric window of 10 as context size, 25 negative samples per positive training instance and a sample probability threshold of 0.0001. The resulting embeddings have a dimension of 200 and the vocabulary size is 478,372. The minimum frequency cut-off was set to 50 for all words and phrases. The embeddings are stored in the binary format of word2vec in encow-adj-n.bin. This format can be loaded by several packages (e.g. the gensim package of Řehůřek, Radim and Petr Sojka (2010)).1 Research carried out in work package A03 of the SFB 833. Deutsche Forschungsgemeinschaft 018mejw64 75650358 SFB 833:  Bedeutungskonstitution - Dynamik und Adaptivität sprachlicher Strukturen

oai:fdat.uni-tuebingen.de:9zce6-v1c45 2026-06-15T16:47:51Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:9zce6-v1c45 Lukassek, Julia Julia Lukassek gnd:1205569987 University of Tübingen Prysłopska, Anna Anna Prysłopska 0000-0002-7634-2782 University of Tübingen Hörnig, Robin Robin Hörnig gnd:1199322741 University of Tübingen Maienborn, Claudia Claudia Maienborn gnd:179660357 University of Tübingen University of Tübingen 2016 linguistics 2016-04-12 2026-06-15 10.57754/FDAT.9zce6-v1c45 10.1007/s10936-016-9466-7 https://fdat.uni-tuebingen.de/communities/crc833/ Creative Commons Attribution Non Commercial No Derivatives 4.0 International This corpus was a control study which tested the telicity of verbs from the self-paced reading study. 200 occurrences of each experimental verb were extracted from the Deutsches Referenzkorpus using Cosmas II. Every occurrence was accompanied by the last two sentences of the preceding context. Only examples containing finite forms of intransitive, literal uses of verbs were chosen for the analysis. Two annotators classified the verbs' occurrences as "telic", "atelic" or "ambiguous", based on standard diagnostics for (a)telicity. Ambiguous cases were discarded; occurrences were labeled "ambiguous" if the two annotators classified them oppositely or agreed on an ambiguous interpretation. The annotation procedure led to a corpus of 2392 occurrences (113–184 per verb) of which 1470 (61%) were telic ones. Research carried out in work package A01 of the SFB 833. Deutsche Forschungsgemeinschaft 018mejw64 75650358 SFB 833:  Bedeutungskonstitution - Dynamik und Adaptivität sprachlicher Strukturen

oai:fdat.uni-tuebingen.de:pkphv-e3t18 2026-06-15T16:47:51Z community-faculty_science

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:pkphv-e3t18 10900.1/a67994b5-19be-4934-9bdb-12fdc0aaef23 Maier, Ruth Ruth Maier 0000-0001-9482-1632 University of Tübingen Leven, Carsten Carsten Leven 0000-0002-6989-6154 University of Tübingen Sanchez-Leon, Emilio Emilio Sanchez-Leon 0000-0002-6717-393X Bayerisches Landesamt für Umwelt Universidad Nacional Autónoma de México Strasser, Daniel Daniel Strasser 0000-0002-0381-2181 Stuttgart Technical University of Applied Sciences Stoll, Maximilian Maximilian Stoll 0000-0001-7846-5076 Swiss Federal Institute of Aquatic Science and Technology Cirpka, Olaf A. Olaf A. Cirpka 0000-0003-3509-4118 University of Tübingen University of Tübingen 2023 hydrogeology geophysics 2023-04-14 2026-06-15 eng 10.57754/FDAT.pkphv-e3t18 10.1007/s10040-022-02458-9 https://fdat.uni-tuebingen.de/communities/faculty_science/ Creative Commons Attribution Share Alike 4.0 International The Hydrogeology group at the Department of Geoscience of the University of Tübingen performs field oriented research at various hydrogeological research site in Southwest Germany. The research focuses on the development of hydrogeological site characterization methods including hydraulic and tracer testing, partly combined with geophysical surveying methods. These data will be the measurement basis of joint inversion and data assimilation methods.  This package contains model and inversion codes for the analysis of pumping tests in a partially penetrating well to resolve vertical aquifer heterogeneity and hydraulic anisotropy.  The stratification of sedimentary aquifers introduces spatial variability in hydraulic conductivity, primarily between individual horizontal layers. On larger scales, the vertical heterogeneity enhances hydraulic anisotropy with the horizontal conductivity typically exceeding the vertical one. We collected pumping test data sets for the estimation of the hydraulic anisotropy of a stratified aquifer with numerical modelling. This package consists of MATLAB-based codes with (i) a numerical forward model for the simulation of radial-symmetric groundwater flow to a well that partially penetrates the aquifer, (ii) a scheme for the inversion of hydraulic tests to estimate hydraulic anisotropy induced by the vertical heterogeneity in stratified aquifers, and (iii) a code for a reproducibility check of field data originating from different pumping tests at the field site "Kappel-Grafenhausen" in the Upper Rhine Valley, Germany. The code package is used for the work described in Maier et al. (2022).

oai:fdat.uni-tuebingen.de:sm2mc-njn64 2026-06-15T16:47:52Z community-crc833

4.5 TUEBINGEN.FDAT oai:fdat.uni-tuebingen.de:sm2mc-njn64 Dima, Corina Corina Dima University of Tübingen University of Tübingen 2017 linguistics 2017-03-14 2026-06-15 10.57754/FDAT.sm2mc-njn64 10.15496/publikation-28485 http://aclweb.org/anthology/W16-1604 10.57754/FDAT.dhnj7-0mb78 https://fdat.uni-tuebingen.de/communities/crc833/ Restricted. The ENglish COMpositionality dataset containing COMpounds (en-comcom) was constructed from two existing compound datasets - the Tratz (2011) dataset and the Ó'Séaghdha (2008) dataset - and a selection of the nominal compounds in the WordNet database. The Tratz (2011) dataset contains 19158 compounds and is part of the semantically-enriched parser described in Tratz (2011) available at http://www.isi.edu/publications/licensed-sw/fanseparser/ The Ó'Séaghdha (2008) contains 1443 compounds and is available at http://www.cl.cam.ac.uk/~do242/Resources/1443_Compounds.tar.gz Additional compounds were collected from the WordNet 3.1 (Fellbaum, 1998) 'data.noun' file. The extracted list contained 18775 compounds. The combination of compounds from the three sources was additionaly pre-processed and frequency-filtered - details in Dima (2019). The final dataset has 27220 compounds. The train, test and dev splits contain 19054, 5444 and 2722 compounds. The train/test/dev files have the following format:                   modifier head compound (e.g. police car police_car) For results of compositionality models evaluated on this dataset see Dima (2016), Dima (2019).                  Dima, Corina. 2015. Reverse-engineering Language: A Study on the Semantic Compositionality of German Compounds. In Proceedings of EMNLP 2015, Lisbon, Portugal, pp. pp. 1637–1642                  [Download paper: https://aclweb.org/anthology/D/D15/D15-1188.pdf]                  - Dima, C. 2016. On the Compositionality and Semantic Interpretation of English Noun Compounds. In Proceedings of the 1st Workshop on Representation Learning for NLP @ ACL 2016, pages 27–39, Berlin, Germany.                  - Dima, C. 2019. Composition Models for the Representation and Semantic Interpretation of Nominal Compounds. PhD thesis. University of Tübingen.                  - Fellbaum, C. 1998. WordNet. Wiley Online Library.                  - Ó Séaghdha, D. 2008. Learning compound noun semantics. PhD thesis, Computer Laboratory, University of Cambridge. Published as University of Cambridge Computer Laboratory Technical Report 735.                  - Tratz, S. 2011. Semantically-enriched parsing for natural language understanding. PhD thesis, PhD Thesis, University of Southern California.   English nominal compounds - compositional distributional representations - semandtic composition Research carried out in work package A03 of the SFB 833. Deutsche Forschungsgemeinschaft 018mejw64 75650358 SFB 833:  Bedeutungskonstitution - Dynamik und Adaptivität sprachlicher Strukturen .eJwlzE9vgjAYgPHv8p6JAQrOchPWsj9xTlwK9GIqrYzwogwwdjN-97nsOf4OzxVGYzRE7oxSGiyoR8gDdUk4Jw70qjYQ-Q60FzXUI0RX6MyktJrU-2AOjYUITqrZ_UHVTAZuDozVcELcNfcl8BTPpW89mYpD6dOzTkWgOfV0ju1jwT1ZvISbPGyzTrilX8f8yJnM2-_Nj-zFUzat2Vu679BWrO8lsuV_yWdi5VYxdvlg-LoWz-4K469VF1jJ46AgmMHtFyfERJg.aszYDA.rk0oRwy8yPyhkGTlEr41nhg8WGs