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Gerwien, Johannes; Stutterheim, Christiane v.; Rummel, Jan, 2022, "A filled-up phonological buffer does not block conceptualization: evidence from a reaction time paradigm [Research Data]", https://doi.org/10.11588/data/6USPPW, heiDATA, V1
This dataset was published as part of the supplementary material for the research article: Gerwien, J. & Stutterheim, C. v. & Rummel, J. (2022). What is the interference in "verbal interference"?. Acta Psychologica (230). We provide reaction time data from two language production... |
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef; Zimmermann, Victor, 2020, "A harmonised testsuite for social media POS tagging (DE)", https://doi.org/10.11588/data/KXLMHN, heiDATA, V1
A harmonised POS testsuite of web data, CMC and Twitter microtext, with word forms and STTS pos tags (+ some additional CMC-specific tags). UD pos tags have been automatically converted, based on the STTS pos tags. The data does not contain (manually corrected) lemma information.... |
Nov 23, 2022 - Institute of Organic Chemistry - AK Mastalerz
Yang, Xuan; Elbert, Sven Michael; Rominger, Frank; Mastalerz, Michael, 2022, "A Series of Soluble Thieno-fused Coronene Nanoribbons of Precise Lengths [Data]", https://doi.org/10.11588/data/30AOAT, heiDATA, V1
Among graphene nanoribbons (GNRs), reports on coronene-based GNRs were very rare, despite the unique optoelectronic properties of coronene. Herein, the synthesis of a series of structurally precise and soluble thieno-fused coronene nanoribbons (CR-1 to CR-4) with up to four coron... |
Feb 4, 2019 - AIPHES
Marasovic, Ana, 2019, "Abstract Anaphora Resolution [Source Code]", https://doi.org/10.11588/data/UDMPY5, heiDATA, V1
Abstract Anaphora Resolution (AAR) aims to find the interpretation of nominal expressions (e.g., this result, those two actions) and pronominal expressions (e.g., this, that, it) that refer to abstract-object-antecedents such as facts, events, plans, actions, or situations. The f... |
Jul 15, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Nastase, Vivi; Kotnis, Bhushan, 2019, "Abstract graphs, abstract paths, grounded paths for Freebase and NELL", https://doi.org/10.11588/data/AVLFPZ, heiDATA, V1
We describe a method for representing knowledge graphs that capture an intensional representation of the original extensional information. This representation is very compact, and it abstracts away from individual links, allowing us to find better path candidates, as shown by the... |
Jul 15, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Nastase, Vivi; Hitschler, Julian, 2019, "ACL word segmentation correction", https://doi.org/10.11588/data/VK99LU, heiDATA, V1
The data in this collection consists of two parallel directories, one ("raw") containing the raw text of 18850 articles from the ACL 2013/02 collection, the other ("re-segmented") the word-resegmented version of these articles, obtained using nematus, a seq2seq neural model used... |
Oct 8, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Ruppenhofer, Josef, 2019, "Affixoid Dataset (DE)", https://doi.org/10.11588/data/QKF4LT, heiDATA, V1, UNF:6:+MGK9lTPTXx7Rclu1BpPnw== [fileUNF]
The dataset contains the manual annotations for the COLING 2018 submission "Distinguishing affixoid formations from compounds" by Josef Ruppenhofer, Michael Wiegand, Rebecca Wilm and Katja Markert. 1788 complex words containing one of 7 German suffixoid candidates (e.g. -hai, -go... |
Jun 16, 2014 - Statistical Natural Language Processing Group
Sokolov, Artem; Jehl Laura; Hieber Felix; Ruppert, Eugen; Riezler, Stefan, 2014, "BoostCLIR: JP-EN Relevance Marked Patent Corpus", https://doi.org/10.11588/data/10001, heiDATA, V1
BoostCLIR is a bilingual (Japanese-English) corpus of patent abstracts, extracted from the MAREC patent data, and the data from the NTCIR PatentMT workshop collections, accompanied with relevance judgements for the task of patent prior-art search. Important: The English side of t... |
Feb 6, 2019 - AIPHES
Heinzerling, Benjamin, 2019, "BPEmb: Pre-trained Subword Embeddings in 275 Languages (LREC 2018)", https://doi.org/10.11588/data/V9CXPR, heiDATA, V1
BPEmb is a collection of pre-trained subword unit embeddings in 275 languages, based on Byte-Pair Encoding (BPE). In an evaluation using fine-grained entity typing as testbed, BPEmb performs competitively, and for some languages better than alternative subword approaches, while r... |
Dec 20, 2023 - NLU anonymized
Christoph Dieterich, 2022, "CARDIO:DE [V1.01]", https://doi.org/10.11588/data/AFYQDY, heiDATA, V7
Version information CARDIO:DE 1.01 Resolved minor annotation bugs Updated TSV format (importable to INCEpTION release > 29.7) Added UIMA CAS corpus version Added annotation layer information files for INCEpTION import ( cardiode_[exp]_dependencies_inception.zip) Abstract: We pres... |
