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131 results for “queries”
DCASE 2024 Task 9: Language-Queried Audio Source Separation | Validation Set
<p>This is the <strong>validation set for Task 9, Language-Queried Audio Source Separation (LASS), in DCASE 2024 Challenge</strong>. </p> <p>This validation split is meant to be used for Task 9 at the scientific challenge DCASE 2024. This split is not meant to be used for training LASS methods. This split is meant to be used for evaluating LASS methods during the model development stage.</p> <p>This validation set consists of 1000 audio files sourced from Freesound [1], uploaded between April and October 2023. Each audio file has been manually annotated with three captions. In the annotation guidance, we instructed annotators to describe the content of audio clips using 5-20 words (similar to the caption style in Clotho [3] and AudioCaps [4] datasets). The tags of each audio file were verified and revised according to the FSD50K [2] sound event categories. Each audio file has been chunked into a 10-second clip and downsampled to 16kHz.</p> <p><strong>== Details ==</strong></p> <p>The audio files in the archives:</p> <ul> <li>lass_validation.zip</li> </ul> <p>and the associated metadata (including tags and captions) in the JSON file:</p> <ul> <li>lass_validation.json</li> </ul> <p>Participants will evaluate their LASS models using synthetic mixture data in the development stage. Specifically, given an audio clip A1 and its corresponding caption C, we select an additional audio clip, A2, to serve as background noise, thereby creating a mixed audio, A3. We anticipate that the LASS system, given A3 and C as inputs, will be able to separate the A1 source. We use the revised tags information to ensure that the two audio clips used in each mix do not share overlapping sound source classes. Three thousand synthetic audio mixtures with signal-to-noise ratios (SNR) ranging from -15dB to 15dB will be generated for the validation of LASS model development. These synthetic mixtures can be generated based on the provided CSV file:</p> <ul> <li>lass_synthetic_validation.csv</li> </ul> <p>The evaluation tool can be found at: https://github.com/Audio-AGI/dcase2024_task9_baseline/blob/main/dcase_evaluator.py</p> <p><strong>== References ==</strong></p> <p>[1] Fonseca E, Pons Puig J, Favory X, et al. Freesound datasets: a platform for the creation of open audio datasets. International Society for Music Information Retrieval (ISMIR), 2017.</p> <p>[2] Fonseca E, Favory X, Pons J, et al. FSD50k: an open dataset of human-labeled sound events. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021, 30: 829-852.</p> <p>[3] Drossos K, Lipping S, Virtanen T. Clotho: An audio captioning dataset. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2020: 736-740.</p> <p>[4] Kim C D, Kim B, Lee H, et al. AudioCaps: Generating captions for audios in the wild. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). 2019: 119-132.</p>
DCASE 2024 Task 9: Language-Queried Audio Source Separation | Development Set
<p><strong>== Description == </strong></p> <p>The development set is composed of audio samples from FSD50K [1] and Clotho v2 [2] datasets. FSD50K contains over 51k audio clips (~100 hours) manually labeled using 200 classes drawn from the AudioSet Ontology. For each audio clip in the FSD50K dataset, we generated one automatic caption for each audio clip by prompting ChatGPT (GPT-4) with its sound event tags. All audio files should be converted to mono 16 kHz audio for training LASS models. </p> <p>Clotho v2: <a href="../records/4783391">https://zenodo.org/records/4783391</a></p> <p>FSD50K: <a href="../records/4060432">https://zenodo.org/records/4060432</a></p> <p>Automatic captions generated for FSD50K:</p> <ul> <li>fsd50k_dev_auto_caption.json</li> <li>fsd50k_eval_auto_caption.json</li> </ul> <p>Prompt for generating captions:</p> <blockquote> <p>I will give you a number of lists containing sound events. Please write an one-sentence audio caption to describe these sounds.</p> <p>Make sure you are using grammatical subject-verb-object sentences. Directly describe the sounds and avoid using the word “heard”. Please don't describe the temporal order of these sound events. The caption should be less than 20 words.</p> </blockquote> <p>In addition to the development set, participants are free to use any external data (including private data) but are not allowed to use audio in Freesound uploaded between April and October 2023. Participants must specify all external resources utilized in their submission in the technical report.</p> <p><strong>== References ==</strong></p> <p>[1] Fonseca E, Favory X, Pons J, et al. FSD50k: an open dataset of human-labeled sound events. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021, 30: 829-852.</p> <p>[2] Drossos K, Lipping S, Virtanen T. Clotho: An audio captioning dataset. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2020: 736-740.</p> <p><strong>== Contact ==</strong></p> <p>Xubo Liu, xubo.liu@surrey.ac.uk</p>
Webis-Context-sensitive-Word-Search-Queries-2022
<pre>This is the dataset created for Language Models as Context-sensitive Word Search Engines at the In2Writing workshop at ACL22. </pre> <p> </p> <p><strong>Cite</strong> </p> <pre><code>@inproceedings{wiegmann:2022, title = "Language Models as Context-sensitive Word Search Engines", author = "Wiegmann, Matti and V{\"{o}}lske, Michael and Potthast, Martin and Stein, Benno", booktitle = "Proceedings of the 1st Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)", month = may, year = "2022", address = "Online", publisher = "Association for Computational Linguistics",</code></pre> <p><strong>Datasets</strong></p> <p>This repository contains two datasets with word search queries. Each word search query consists of a token n-gram with one wildcard token ([MASK]). The answers to each query are the most likely token to replace the mask. All queries originate from wikitext-103 and CLOTH, the respected source is annotated for each query.</p> <p>The <em>original-token</em> dataset lists exactly one top answer for each query. The <em>ranked-answers</em> dataset lists multiple, sorted answers in three relevance categories, where 3 is the most relevant. Please refer to the citation for more details.</p>
Exact structure match queries against BindingDB between September 2004 and August 2012
<p>Exact structure match queries against BindingDB between September 2004 and August 2012</p> <p>The queries were generated by users of the BindingDB web interface between September 2004 and mid-August of 2012. Structures were sketched using Marvin.</p> <p>If you use this data set, please cite:</p> <p> Liu T, Lin Y, Wen X, Jorissen RN, Gilson MK.<br> BindingDB: a web-accessible database of experimentally determined<br> protein-ligand binding affinities.<br> Nucleic Acids Res. 2007 Jan;35(Database issue):D198-201.<br> doi: 10.1093/nar/gkl999<br> Epub 2006 Dec 1<br> PMID: 17145705<br> PMCID: PMC1751547<br> https://doi.org/10.1093%2Fnar%2Fgkl999</p> <p>The included files are:</p> <p>README<br> ------</p> <p>A text file with more details about the data sets and their provenance.</p> <p>exact.dat.zstd<br> --------------</p> <p>The processed data set with 3,414,228 queries, one query per line. The file is compressed using Zstandard. The queries are a combination of CXSMILES, non-standard SMILES, and non-SMILES strings.</p> <p>BindingDB_exact.dat<br> -------------------</p> <p>A cleaned-up subset with 119,883 entries, one entry per line. Each entry has two columns, separated by a tab. The first column is the (possibly cleaned-up) CXSMILES from the source data, the second is the number of times the CXSMILES occurs in the source data. Each CXSMILES is present only once in the data set.</p> <p>NOTE: the CXSMILES have not be canonicalized. Canonicalization using RDKit 2021.09.4 results in 94,362 unique queries, but causes the extended CXSMILES annotations to disappear.</p> <p>bindingdb_cleanup.py<br> --------------------</p> <p>The Python program used to convert exact.dat.zstd to BindingDB_exact.dat.</p> <p>History<br> =======</p> <p>15 August 2012<br> --------------</p> <p>Contribution to the SQC.</p> <p>Tiqing Lui</p> <p>18 Aug 2012<br> -----------</p> <p>Initial import into the SQC</p> <p>Andrew Dalke</p> <p>28 Aug 2022<br> -----------</p> <p>Ported bindingdb_cleanup.py to Python 3.</p> <p>Added cleanup methods to add brackets to "(O-)", "C@@", "nH", and "NH" when appropriate.</p> <p>Simplified bindingdb_cleanup.py by dropping support for tools other than RKit.</p> <p>Updated for distribution on Zenodo.</p> <p>Andrew Dalke</p> <p> </p>
Bird predation on Roseau cane scale as revealed by a web image search and querying a citizen monitoring database
<p>NA</p>
Publications Office SPARQL queries for RDF benchmark
<p>This dataset contains the queries used for the benchmarking of the RDF stores for the EU Publications Office (PO).</p> <p>The queries are divided in three categories according to the types of queries. The initial queries from PO where validated using Jena tool to make them compliant with any SPARQL endpoint. </p>
Supplementary Material for Nested Segmentation of Web Search Queries
<p>1. Query test of SGCL12 [SGCL12QueryTestSet.txt]</p> <p>2. Outputs of 16 nesting algorithms on the query test set of SGCL12 [Input flat segmention: Saha Roy et al., SIGIR 2012] [Nested Segmentation Outputs SGCL12.zip]</p> <p>3. Query set of TREC-WT [TREC-WTQueryTestSet.txt]</p> <p>4. Outputs of 16 nesting algorithms on the query test set of TREC-WT [Input flat segmention: Saha Roy et al., SIGIR 2012] [Nested Segmentation Outputs TREC-WT.zip]</p> <p>5. Code and executables for generating the nested segmentations for a set of queries [Code and execs for generating nested segmentations.zip]</p> <p>6. Code and executables for IR-based evaluation of a nested segmentation [Code and execs for IR evaluation of a nested segmentation.zip]</p> <p>7. Readme.txt</p>
DCASE 2024 Task 9: Language-Queried Audio Source Separation | Evaluation Set
<p>This is the <strong>evaluation set for Task 9, Language-Queried Audio Source Separation (LASS), in DCASE 2024 Challenge</strong>. </p> <p>This evaluation set is meant to be used for Task 9 at the scientific challenge DCASE 2024. This split is not meant to be used for training LASS methods. This split is meant to be used for evaluating LASS methods in the final testing & ranking stage. All audio clips are sourced from Freesound, uploaded between April and October 2023. Each audio file has been segmented into 10-second clips and converted to mono 16 kHz.</p> <p>This evaluation set consists of<strong> evaluation set (synth)</strong> and an <strong>evaluation set (real)</strong>. </p> <p><strong>== Evaluation set (synth) ==</strong></p> <p>This evaluation set is created using 1,000 audio clips. Each clip is annotated with three captions describing the content of the clip. We created 3,000 synthetic mixtures with signal-to-noise ratios (SNR) ranging from -15 to 15 dB. Each synthetic mixture includes one natural language query and its corresponding target source. We used annotated tag information to ensure that the two audio clips used in each mix do not share overlapping sound source classes. The original audio files used to create these mixtures are not released. The mixtures and language queries are available for evaluation.</p> <p>The audio files in the archives:</p> <ul> <li>lass_evaluation_synth.zip</li> </ul> <p>and the associated metadata (including audio filename and text queries) in the CSV file:</p> <ul> <li>lass_synthetic_evaluation.csv</li> </ul> <p><strong>== Evaluation set (real) ==</strong></p> <p>This evaluation set consists of 100 audio clips. Each audio clip contains at least two overlapping sound sources. For each audio clip, we manually annotated their component sources using text descriptions, so that each clip can be used as a 'mixture' from which to extract one or more of the component sources based on a text query. Each audio clip in evaluation (real) was labeled with two such text queries.</p> <p>The audio files in the archives:</p> <ul> <li>lass_evaluation_real.zip</li> </ul> <p>and the associated metadata (including audio filename and text queries) in the CSV file:</p> <ul> <li>lass_real_evaluation.csv</li> </ul>
Search-Based Test Data Generation for SQL Queries: Appendix
<p>The appendix of our ICSE 2018 paper "Search-Based Test Data Generation for SQL Queries: Appendix".</p> <p>The appendix contains:</p> <ul> <li>The queries from the three open source systems we used in the evaluation of our tool (the industry software system is not part of this appendix, due to privacy reasons)</li> <li>The results of our evaluation.</li> <li>The source code of the tool. Most recent version can be found at https://github.com/SERG-Delft/evosql.</li> <li>The results of the tuning procedure we conducted before running the final evaluation.</li> </ul>
MTG-QBH: Query By Humming dataset
<p>This dataset includes 118 recordings of sung melodies. The recordings were made as part of the experiments on Query-by-Humming (QBH) reported in the following article:</p> <blockquote> <p>J. Salamon, J. Serrà and E. Gómez, "<a href="http://mtg.upf.edu/node/2657">Tonal Representations for Music Retrieval: From Version Identification to Query-by-Humming</a>", International Journal of Multimedia Information Retrieval, special issue on Hybrid Music Information Retrieval, In Press (accepted Nov. 2012). </p> </blockquote> <p>The recordings were made by 17 different subjects, 9 female and 8 male, whose musical experience ranged from none at all to amateur musicians. Subjects were presented with a list of songs out of which they were asked to select the ones they knew and sing part of the melody. The subjects were aware that the recordings will be used as queries in an experiment on QBH. There was no restriction as to how much of the melody should be sung nor which part of the melody should be sung, and the subjects were allowed to sing the melody with or without lyrics. The subjects did not listen to the original songs before recording the queries, and the recordings were all sung a capella without any accompaniment nor reference tone. To simulate a realistic QBH scenario, all recordings were done using a basic laptop microphone and no post-processing was applied. The duration of the recordings ranges from 11 to 98 seconds, with an average recording length of 26.8 seconds. </p> <p>In addition to the query recordings, three meta-data files are included, one describing the queries and two describing the music collections against which the queries were tested in the experiments described in the aforementioned article. Whilst the query recordings are included in this dataset, audio files for the music collections listed in the meta-data files are NOT included in this dataset, as they are protected by copyright law. If you wish to reproduce the experiments reported in the aforementioned paper, it is up to you to obtain the original audio files of these songs.</p> <p>All subjects have given their explicit approval for this dataset to be made public.</p> <p>Please Acknowledge MTG-QBH in Academic Research</p> <p><strong>Using this dataset</strong></p> <p>When the MTG-QBH dataset is used for academic research, we would highly appreciate if scientific publications of works partly based on the MTG-QBH dataset cite the above publication.</p> <p>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.</p> <p> </p> <p><a href="https://www.upf.edu/web/mtg/mtg-qbh">https://www.upf.edu/web/mtg/mtg-qbh</a></p>
Process plant data integration and querying
<p>This data set includes:</p> <ul> <li>Process plant data derived from heterogeneous sources</li> <li>An OWL ontology of the entities in the data sources</li> <li>Mapping for data in the sources to the ontology (<em>done using Cellfi</em>e,a <em>Protégé plugin. Also save as .json to use</em>)</li> <li>Data integrated from all the sources</li> <li>Sample SPARQL queries (<em>Q5 and Q6</em>)</li> </ul> <p> </p>
query suggestion with siri - query suggestions for instagram accounts
<p>Das Datenset enthält Query Suggestions zu 20 Instragram-Accounts bzw. Personen oder Firmen dahinter. (Instagram, Cristiano Ronaldo, Ariana Grande, Selena Gomez, The Rock, Kim Kardashian West, Kylie Jenner, Beyoncé, Taylor Swift, Leo Messi, Neymar jr, Kendall Jenner, Justin Bieber, National Geographic, Barbie, Khloe Kardashian, Jennifer Lopez, Miley Cyrus, Nike, Katy Perry)</p> <p>Die Datenerhebung erfolgte vom 26.05.2019 - 23.06.2019. Enthalten sind Vorschläge der Suchmaschinen Bing, DuckDuckGo, Google und der Suche in Siri (an einem Tablet und in einer XCode Simulation), wobei die Anzahl der zurückgelieferten Vorschläge variiert.</p> <p>Das Datenset enthält folgende Spalten: Plattform, Suchbegriff, Datum, Vorschlag Position</p> <p> </p>
SPARQL-Queries: Patterns in modeling and querying a knowledge graph for literary history
<p>All SPARQL queries documented here refer to the SPARQL endpoint: <u><a href="https://query.mimotext.uni-trier.de/">https://query.mimotext.uni-trier.de</a></u>. The queries are supplement to the following preprint: <span><a href="https://doi.org/10.5281/zenodo.12080340">https://doi.org/10.5281/zenodo.12080340</a></span>.</p> <ul> <li>Query 0, Fig 3: <u><a href="https://query.mimotext.uni-trier.de/#PREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0A%23defaultView%3AGraph%0ASELECT%20%3Fitem1%20%3Fitem1Label%20%3Fitem2%20%3Fitem2Label%20%3FedgeLabel%20%0AWITH%20%7B%0A%20%20SELECT%20%3Fitem1%20WHERE%20%7B%0A%20%20%20%20VALUES%20%3Fitem1%20%7B%20mmd%3AQ1011%20mmd%3AQ981%20mmd%3AQ2%20mmd%3AQ3039%20mmd%3AQ38%20mmd%3AQ3126%20mmd%3AQ3335%20mmd%3AQ3259%20mmd%3AQ3906%7D%0A%20%20%7D%0A%7D%20AS%20%25item1%0AWITH%20%7B%0A%20%20SELECT%20%28%3Fitem1%20AS%20%3Fitem2%29%20WHERE%20%7B%0A%20%20%20%20INCLUDE%20%25item1.%0A%20%20%7D%0A%7D%20AS%20%25item2%0AWHERE%20%7B%0A%20%20INCLUDE%20%25item1.%0A%20%20INCLUDE%20%25item2.%0A%20%20%3Fitem1%20%3Fwdt%20%3Fitem2.%0A%20%20%3Fedge%20wikibase%3AdirectClaim%20%3Fwdt%3B%0A%20%20%20%20%20%20%20%20a%20wikibase%3AProperty.%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D" target="_blank" rel="noopener">Authors (here: ‘Voltaire’) and works (here: ‘Le Micromégas’) in subject position shown as Graph</a></u></li> <li>Query 1: <u><a href="https://query.mimotext.uni-trier.de/#PREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIx%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0ASELECT%20%3Fsubject%20%28COUNT%28%3Fo%29%20as%20%3Fcounts%29%0AWHERE%20%7B%0A%20%20VALUES%20%28%3Fp%20%3Fo%29%20%7B%20%28mmdt%3AP2%20mmd%3AQ2%29%20%28mmdt%3AP11%20mmd%3AQ11%29%20%28mmdt%3AP2%20mmd%3AQ20%29%20%28mmdt%3AP2%20mmd%3AQ26%29%20%7D%0A%20%20%3Fitem%20%3Fp%20%3Fo.%0A%20%20BIND%28IF%28%3Fo%20%3D%20mmd%3AQ2%2C%20%22novels%22%2C%20%0A%20%20%20%20%20%20%20%20%20%20IF%28%3Fo%20%3D%20mmd%3AQ11%2C%20%22authors%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20IF%28%3Fo%20%3D%20mmd%3AQ20%2C%20%22thematic%20concepts%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20IF%28%3Fo%20%3D%20mmd%3AQ26%2C%20%22spatial%20concepts%22%2C%20%22none%22%29%0A%20%20%20%20%20%20%20%20%20%20%20%29%0A%20%20%20%20%20%20%20%20%20%20%29%0A%20%20%20%20%20%20%20%20%20%29%20as%20%3Fsubject%29%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%0A%7DGROUP%20BY%20%3Fo%20%3Fsubject" target="_blank" rel="noopener">Count of novels, authors, thematic concepts and spatial concepts</a></u></li> <li>Query 2: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3A%20Narrative%20locations%20of%20literary%20works%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20%3Fitem%20%3FitemLabel%20%3FnarrativeLoc%20%3FnarrativeLocLabel%0AWHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%20%23item%20is%20instance%20of%20literary%20work%0A%20%20%20%20%20%20%20%20mmdt%3AP32%20%3FnarrativeLoc.%20%23item%20has%20narrative%20location%28s%29%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%0A%20%20%7D" target="_blank" rel="noopener">Narrative locations of literary works</a></u></li> <li>Query 3: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3A%20Novels%20set%20in%20%27imaginary%20place%27%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%0AWHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%20%23item%20is%20instance%20of%20literary%20work%0A%20%20%20%20%20%20%20%20mmdt%3AP32%20mmd%3AQ3371.%20%23%20item%20has%20narrative%20location%20%27imaginary%20place%27%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%20%20%0A%0A%7D" target="_blank" rel="noopener">Novels set in ‘imaginary place’</a></u></li> <li>Query 4: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3ANovels%20that%20have%20theme%20%27miracle%27%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%0AWHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%20%23item%20is%20instance%20of%20literary%20work%0A%20%20%20%20%20%20%20%20mmdt%3AP36%20mmd%3AQ2990.%20%23%20item%20is%20about%20miracle%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%20%20%0A%0A%7D" target="_blank" rel="noopener">Novels that have theme ‘miracle’</a></u></li> <li>Query 5: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3ANovels%20published%20in%20Paris%20between%201780%20and%201790%20that%20have%20theme%20%27philosophy%27%20%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20%3Fitem%20%3FitemLabel%20%3Fyear%0AWHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%20%23item%20is%20instance%20of%20literary%20work%0A%20%20%20%20%20%20%20%20mmdt%3AP10%20mmd%3AQ3521%3B%20%23item%20was%20published%20in%20Paris%0A%20%20%20%20%20%20%20%20mmdt%3AP36%20mmd%3AQ3039%3B%20%23item%20is%20about%20philosophy%0A%20%20%20%20%20%20%20%20mmdt%3AP9%20%3Fdate.%20%23item%20has%20publication%20date.%0A%0A%20%20FILTER%28%3Fdate%20%3E%3D%20%221780%22%5E%5Exsd%3AdateTime%20%26%26%20%3Fdate%20%3C%3D%20%221790%22%5E%5Exsd%3AdateTime%29.%0A%20%20BIND%28YEAR%28%3Fdate%29%20as%20%3Fyear%29.%0A%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%20%20%0A%0A%7D" target="_blank" rel="noopener">Novels published in Paris between 1780 and 1790 that have theme ‘philosophy’</a></u></li> <li>Query 6: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AQuery%20to%20retrieve%20some%20data%20about%20the%20MiMoTextBase%20such%20as%20Authors%2C%20Novels%2C%20publicationyears%2C%20tonality%20etc.%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20%3Fbgrf%20%3Fitem%20%3FitemLabel%20%3FauthorLabel%20%3Fyear%20%3Fnarrpers%20%3Ftonality%20%3Fpages%20%3Fdist_format%20WHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2.%20%23item%20is%20instance%20of%20literary%20work%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP5%20%3Fauthor%7D%20%23item%20has%20author%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP4%20%3Ftitle%7D%20%23item%20has%20title%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP22%20%3Fbgrf%7D%20%20%23item%20has%20identifier%20in%20the%20bibliographic%20metadata%3F%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP9%20%3Fdate%7D%20%23item%20has%20publication%20date%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP27%20%3Fnarrpers%7D%20%23item%20has%20narrative%20form%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP31%20%3Ftonality%7D%20%23item%20has%20tonality%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP25%20%3Fpages%7D%20%23item%20has%20page%20information%20%28optionally%29%0A%20%20OPTIONAL%20%7B%20%3Fitem%20mmdt%3AP26%20%3Fdist_format%7D%20%23item%20has%20distribution%20format%20%28optionally%29%0A%20%20BIND%28YEAR%28%3Fdate%29%20as%20%3Fyear%29%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2C%20fr%22.%20%7D%0A%7D%20ORDER%20BY%20%3Fyear" target="_blank" rel="noopener">Query to retrieve some data about the MiMoTextBase such as Authors, Novels, publicationyears, tonality etc.</a></u></li> <li>Query 7, Fig. 5: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AThemes%20occuring%20in%20novels%20of%20intention%20satire%0A%23defaultView%3ABubbleChart%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0ASELECT%20%3Ftheme%20%28SAMPLE%28%3FthemeLabel%29%20as%20%3Fname%29%20%20%28count%28%2A%29%20as%20%3Fcount%29%0AWHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%20%23%20item%20is%20instance%20of%20literary%20work%0A%20%20%20%20%20%20%20%20mmdt%3AP39%20mmd%3AQ3906%3B%20%23novel%20has%20intention%20satire%0A%20%20%20%20%20%20%20%20mmdt%3AP36%20%3Ftheme.%20%23novel%20has%20theme%0A%20%20%20%20%20%20%3Ftheme%20rdfs%3Alabel%20%3FthemeLabel%20.%0A%20%20%20%20%20%20FILTER%20%28LANG%28%3FthemeLabel%29%20%3D%20%22en%22%29%20.%0A%7D%0AGROUP%20BY%20%3Ftheme%0AORDER%20BY%20DESC%28%3Fcount%29" target="_blank" rel="noopener">Themes occuring in novels of intention satire</a></u></li> <li>Query 8: <u><a href="https://query.mimotext.uni-trier.de/#%23defaultView%3ABarChart%0A%23title%3ARatio%20of%20the%20theme%20%27nature%27%20over%20time%0A%23count%20of%20%27nature%27%20%28countNature%29%20as%20a%20novel%20theme%20in%20relation%20to%20the%20number%20of%20novels%20published%20per%20year%20%28countAll%29%3B%20ratio%2C%20as%20novel%20production%20is%20rising%20strongly%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0ASELECT%20%3Fdate%20%28%3FcountNature%20%2F%20%3FcountAll%20AS%20%3Frel%29%20%20%3FcountNature%20%3FcountAll%20%20WHERE%20%7B%0A%20%20%7B%0A%20%20%20%20%20%20%20%20SELECT%20%3Fdate%20%28COUNT%28%2A%29%20AS%20%3FcountNature%29%20WHERE%20%7B%0A%20%20%20%20%20%20%20%20%3Fitem%20mmdt%3AP9%20%3Fdate%3B%0A%20%20%20%20%20%20%20%20%20%20mmdt%3AP36%20mmd%3AQ3005.%0A%20%20%20%20BIND%28YEAR%28%3Fdate%29%20as%20%3Fyear%29%0A%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20GROUP%20BY%20%3Fdate%0A%20%20%7D%0A%20%20%7B%0A%20%20%20%20%20%20%20%20SELECT%20%3Fdate%20%28COUNT%28%2A%29%20AS%20%3FcountAll%29%20WHERE%20%7B%0A%20%20%20%20%20%20%20%20%3Fitem%20mmdt%3AP9%20%3Fdate%3B%0A%20%20%20%20%20%20%20%20%20%20mmdt%3AP36%20%3Ftopic.%0A%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20GROUP%20BY%20%3Fdate%0A%20%20%7D%0A%7D" target="_blank" rel="noopener">Ratio of the theme ‘nature’ over time</a></u></li> <li>Query 9: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AThematic%20concepts%20of%20novels%20referenced%20by%20%E2%80%98Topic%20Modeling%E2%80%99%0A%23defaultView%3ABubbleChart%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0APREFIX%20mmpr%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Freference%2F%3E%0APREFIX%20mmps%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fstatement%2F%3E%0APREFIX%20prov%3A%20%3Chttp%3A%2F%2Fwww.w3.org%2Fns%2Fprov%23%3E%0A%0ASELECT%20%3FthemeLabel%20%28COUNT%28%2A%29%20AS%20%3Fcount%29%20WHERE%20%7B%0A%20%20%3Fstatement%20mmps%3AP36%20%3Ftheme%3B%0A%20%20%20%20%20%20%20%20prov%3AwasDerivedFrom%20%3Frefnode.%0A%20%20%3Frefnode%20mmpr%3AP18%20mmd%3AQ21.%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D%0AGROUP%20BY%20%3FthemeLabel" target="_blank" rel="noopener">Thematic concepts of novels referenced by ‘Topic Modeling’</a></u></li> <li>Query 10, Fig. 6: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AThematic%20statements%20derived%20from%20%E2%80%98topic%20modeling%E2%80%99%20and%20the%20bibliography%0A%23Statements%20on%20consistent%20topics%20in%20novels%20from%20both%20sources%3A%20Topic%20Modeling%20%26%20bibliographic%20metadata%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%20%0APREFIX%20mmps%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fstatement%2F%3E%0APREFIX%20mmpr%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Freference%2F%3E%0APREFIX%20mmp%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2F%3E%0A%0ASELECT%20%3Fnovel%20%3FnovelLabel%20%3FtopicLabel%20%3FBGRF_plot_theme%20WHERE%0A%7B%20%20%20%0A%20%20%20%20%3Fnovel%20mmp%3AP36%20%3Fstatement.%0A%20%20%20%20%3Fstatement%20mmps%3AP36%20%3Ftopic.%0A%20%20%20%20%3Fstatement%20prov%3AwasDerivedFrom%2Fmmpr%3AP18%20mmd%3AQ21.%20%23reference%20statement%20uses%20%27P18%27%3D%27stated%20in%27%20topic%20modeling%0A%20%20%20%20%3Fstatement%20prov%3AwasDerivedFrom%2Fmmpr%3AP18%20mmd%3AQ1.%20%23reference%20statement%20uses%20%27P18%27%3D%27stated%20in%27%20bibliographie%20%20%0A%20%20%20%20%3Fnovel%20mmdt%3AP30%20%3FBGRF_plot_theme.%20%23statement%20in%20the%20BGRF%20about%20the%20plot%20theme.%0A%20%20%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D" target="_blank" rel="noopener">Thematic statements referenced by ‘topic modeling’ and the bibliography</a></u></li> <li>Query 11: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AOverview%20over%20controlled%20vocabularies%0A%23%20Query%20to%20retrieve%20the%20different%20controlled%20vocabularies%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20%3Fvoc%20%3FvocLabel%20%28COUNT%28%3FvocLabel%29%20as%20%3Fcount%29%20%28COUNT%28%3Fwikimatch%29%20as%20%3Fwikimatch%29%0AWHERE%20%7B%0A%20%20%20%3Fitem%20mmdt%3AP37%20%3Fvoc.%0A%20%20%20%3Fvoc%20mmdt%3AP2%2Fmmdt%3AP1%20mmd%3AQ17.%0A%20%20%20OPTIONAL%7B%0A%20%20%20%20%20values%20%3Fwiki%20%7Bmmdt%3AP13%20mmdt%3AP16%7D%0A%20%20%20%20%20%3Fitem%20%3Fwiki%20%3Fwikimatch%7D%0A%20%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%0A%20%20%7D%0AGROUP%20BY%20%3Fvoc%20%3FvocLabel%0AORDER%20BY%20DESC%28%3Fcount%29" target="_blank" rel="noopener">Overview over controlled vocabularies</a></u></li> <li>Query 12: <u><a href="https://query.mimotext.uni-trier.de/#%23%20get%20combinations%20of%20narrative%20Form%20and%20intention%20per%20year%0A%23defaultView%3ABarChart%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%20%0A%0ASELECT%20%3Fyear%20%28COUNT%28%2A%29%20as%20%3Fcount%29%20%3FnarrFormTone%0A%20%20WHERE%7B%0A%20%20%20%20%3Fitem%20mmdt%3AP9%20%3Fpublicationdate.%20%23%20get%20publication%20date%0A%20%20%20%20%3Fitem%20mmdt%3AP38%20%3Ftone.%20%23%20get%20intention%0A%20%20%20%20BIND%28str%28YEAR%28%3Fpublicationdate%29%29%20as%20%3Fyear%29.%20%23%20extract%20year%20from%20pubdate%0A%20%20%20%20%3Fitem%20mmdt%3AP33%20%3FnarrForm.%20%23%20get%20narrative%20form%20%20%20%0A%20%20%20%20%3Ftone%20rdfs%3Alabel%20%3FtoneLabel.%0A%20%20%20%20FILTER%28LANG%28%3FtoneLabel%29%20%3D%20%22en%22%29.%0A%20%20%20%20%3FnarrForm%20rdfs%3Alabel%20%3FnarrFormLabel.%0A%20%20%20%20FILTER%28LANG%28%3FnarrFormLabel%29%20%3D%20%22en%22%29.%20%0A%20%20%20%20BIND%28CONCAT%28STR%28%3FnarrFormLabel%29%2C%20%22%20--%20%22%20%2C%20STR%28%3FtoneLabel%29%29%20as%20%3FnarrFormTone%29.%0A%20%20%7D%0AGROUP%20BY%20%3Fyear%20%3FnarrFormTone%0AHAVING%20%28%3Fcount%20%3E%201%29%0AORDER%20BY%20%3Fyear" target="_blank" rel="noopener">Combinations of narrative Form and intention per year</a></u></li> <li>Query 13: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3ATopic%20labels%20in%20English%2C%20French%20and%20German%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0A%0ASELECT%20DISTINCT%20%3Ftopic%20%3FtopicLabel_EN%20%3FtopicLabel_FR%20%3FtopicLabel_DE%20WHERE%20%7B%0A%20%20%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%0A%20%20%20%20%20%20%20%20mmdt%3AP36%20%3Ftopic.%0A%20%0A%20%20%3Ftopic%20rdfs%3Alabel%20%3FtopicLabel_EN.%0A%20%20%3Ftopic%20rdfs%3Alabel%20%3FtopicLabel_FR.%0A%20%20%3Ftopic%20rdfs%3Alabel%20%3FtopicLabel_DE.%0A%20%20%0A%20%20FILTER%28LANG%28%3FtopicLabel_EN%29%20%3D%20%22en%22%29.%0A%20%20FILTER%28LANG%28%3FtopicLabel_FR%29%20%3D%20%22fr%22%29.%0A%20%20FILTER%28LANG%28%3FtopicLabel_DE%29%20%3D%20%22de%22%29.%0A%0A%7D" target="_blank" rel="noopener">Topic labels in English, French and German using rdfs:label and Filter</a></u></li> <li>Query 14: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3A%20Topic%20labels%20in%20English%2C%20French%20and%20German%0APREFIX%20mmd%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%20%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20DISTINCT%20%3Ftopic%20%3FtopicLabel_EN%20%3FtopicLabel_FR%20%3FtopicLabel_DE%0A%20%20%20WHERE%20%7B%0A%20%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2%3B%20%0A%20%20%20%20%20%20%20%20%20mmdt%3AP36%20%3Ftopic.%20%20%0A%20%20%20%20%20%0A%20%20%20%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%0A%20%20%20%20%20%20%20%20%20%20%20%20%3Ftopic%20rdfs%3Alabel%20%3FtopicLabel_EN.%0A%20%20%20%20%20%7D%0A%20%20%20%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22de%22.%0A%20%20%20%20%20%20%20%20%20%20%20%20%3Ftopic%20rdfs%3Alabel%20%3FtopicLabel_DE.%0A%20%20%20%20%20%7D%20%0A%20%20%20%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22fr%22.%0A%20%20%20%20%20%20%20%20%20%20%20%20%3Ftopic%20rdfs%3Alabel%20%3FtopicLabel_FR.%0A%20%20%20%20%20%7D%20%0A%20%20%20%0A%20%20%20%7D" target="_blank" rel="noopener">Topic labels in English, French and German using Wikibase Label Service</a></u></li> <li>Query 15: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3ALabels%20entered%20on%20wikidata-entry%20%27Voltaire%27%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20%28LANG%28%3FVoltaireLabels%29%20as%20%3Flang%29%20%3FVoltaireLabels%20%0AWHERE%20%7B%20%0A%20%20%0A%20%20mmd%3AQ981%20mmdt%3AP13%20%3FwikiDataEntity.%20%23%20Voltaire%20has%20a%20wikidata%20match.%0A%0A%20%20%23Federated%20Query%20-%3E%20Wikidata%0A%20%20SERVICE%20%3Chttps%3A%2F%2Fquery.wikidata.org%2Fsparql%3E%20%7B%0A%20%20%3FwikiDataEntity%20rdfs%3Alabel%20%3FVoltaireLabels.%0A%20%20%7D%20%20%20%20%20%20%20%20%20%20%20%20%20%20%0A%7D%0AORDER%20BY%20%3Flang" target="_blank" rel="noopener">Labels entered on wikidata-entry ‘Voltaire’</a></u></li> <li>Query 16, Fig. 9: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3ANarrative%20locations%20of%20the%20novels%20on%20a%20map%0A%23defaultView%3AMap%7B%22markercluster%22%3A%22true%22%7D%0APREFIX%20wd%3A%20%3Chttp%3A%2F%2Fwww.wikidata.org%2Fentity%2F%3E%20%23wikidata%20wd%0APREFIX%20wdt%3A%20%3Chttp%3A%2F%2Fwww.wikidata.org%2Fprop%2Fdirect%2F%3E%20%23wikidata%20wdt%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0ASELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%20%3Fnarr_loc%20%3Fnarr_locLabel%20%3FWikiDataEntity%20%3FcoordinateLocation%0AWHERE%20%7B%20%3Fitem%20mmdt%3AP32%20%3Fnarr_loc.%0A%20%20%3Fnarr_loc%20mmdt%3AP13%20%3FWikiDataEntity.%0A%20%20%23Federated%20Query%20-%3E%20Wikidata%0A%20%20SERVICE%20%3Chttps%3A%2F%2Fquery.wikidata.org%2Fsparql%3E%20%7B%0A%20%20%20%20%20%20%20%20%3FWikiDataEntity%20wdt%3AP625%20%3FcoordinateLocation%0A%20%20%7D%20%20%20%20%20%20%20%20%20%20%20%20%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22%20.%20%7D%0A%7D" target="_blank" rel="noopener">Narrative location with geo coordinate locations via federated query</a></u></li> <li>Query 17: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AAlternative%20Labels%20of%20author%20names%20via%20%E2%80%98federated%E2%80%99%20queries%E2%80%99%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20DISTINCT%20%3Fauthor%20%3FauthorLabel%20%3FwikidataEntity%20%3Faltname%0AWHERE%20%7B%0A%20%20%20%20%20%20%20%20%20%3Fitem%20mmdt%3AP5%20%3Fauthor.%0A%20%20%20%20%20%20%3Fauthor%20mmdt%3AP13%20%3FwikidataEntity.%20%20%23exact%20match%0A%20%0A%20%20%20%20%20%20%23Federated%20Query%20-%3E%20Wikidata%0ASERVICE%20%3Chttps%3A%2F%2Fquery.wikidata.org%2Fsparql%3E%20%7B%0A%20%20%20%20%20%20%20%20%20%3FwikidataEntity%20skos%3AaltLabel%20%3Faltname%0A%20%20%20%20%20%20%7D%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20SERVICE%20wikibase%3Alabel%20%7B%0A%20%20%20%20%20%20%20%20%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22%20.%0A%20%20%20%20%20%20%7D%0A%7D%0ALIMIT%201000" target="_blank" rel="noopener">Alternative Labels of author names via ‘federated’ queries’</a></u></li> <li>Query 18, Fig. 10: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AMiMoText%20novels%20with%20URL%20to%20Biblioth%C3%A8que%20nationale%20de%20France%20%0A%23defaultView%3AImageGrid%0APREFIX%20wd%3A%20%3Chttp%3A%2F%2Fwww.wikidata.org%2Fentity%2F%3E%20%23wikidata%20prefix%20definition%20for%20entity%0APREFIX%20wdt%3A%20%3Chttp%3A%2F%2Fwww.wikidata.org%2Fprop%2Fdirect%2F%3E%20%23wikidata%20prefix%20definition%20for%20property%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%20%23mimotext%20prefix%20for%20entity%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%20%23mimotext%20prefix%20for%20property%0A%0ASELECT%20%3Fitem%20%3FitemLabel%20%3Fwikidata%20%3Fbnfurl%20%3Fimage%20%0AWHERE%20%7B%0A%20%20%3Fitem%20mmdt%3AP2%20mmd%3AQ2.%0A%20%20%3Fitem%20mmdt%3AP13%20%3Fwikidata.%0A%20%20%3Fitem%20rdfs%3Alabel%20%3FitemLabel%20.%0A%20%20FILTER%28lang%28%3FitemLabel%29%20%3D%20%22en%22%29%0A%20%20SERVICE%20%3Chttps%3A%2F%2Fquery.wikidata.org%2Fsparql%3E%20%7B%0A%20%20%20%20%3Fwikidata%20wdt%3AP268%20%3Fbnfid.%0A%20%20%20%20OPTIONAL%7B%20%3Fwikidata%20wdt%3AP18%20%3Fimage.%7D%0A%20%20%20OPTIONAL%7B%20wd%3AP268%20wdt%3AP1630%20%3Fformatterurl.%7D%0A%20%20%20BIND%28IRI%28REPLACE%28%3Fbnfid%2C%20%27%5E%28.%2B%29%24%27%2C%20%3Fformatterurl%29%29%20AS%20%3Fbnfurl%29.%0A%20%20%7D%20%20%20%20%20%20%20%20%20%0A%7D" target="_blank" rel="noopener">Finding Identifiers on other Knowledge Graphs, for example Bibliothèque nationale de France ID</a></u></li> <li>Query 19, Fig. 11: <u><a href="https://query.mimotext.uni-trier.de/#%23title%3AInfluence%20networks%20of%20authors%20via%20%27federated%20query%27%0A%23defaultView%3AGraph%0APREFIX%20wd%3A%3Chttp%3A%2F%2Fwww.wikidata.org%2Fentity%2F%3E%20%23wikidata%20entity%0APREFIX%20wdt%3A%3Chttp%3A%2F%2Fwww.wikidata.org%2Fprop%2Fdirect%2F%3E%20%23wikidata%20property%0A%0APREFIX%20mmd%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fentity%2F%3E%0APREFIX%20mmdt%3A%3Chttp%3A%2F%2Fdata.mimotext.uni-trier.de%2Fprop%2Fdirect%2F%3E%0A%0ASELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%20%3FauthorLabel%20%3Finfluencedby%20%3Fimage%20%3Fname%0AWHERE%20%7B%0A%20%20%20%20%20%20%3Fitem%20mmdt%3AP5%20%3Fauthor.%0A%20%20%20%20%20%20%3Fauthor%20mmdt%3AP13%20%3FWikidataEntity.%20%20%23exact%20match%0A%20%20%20%20%20%20%0A%23Federated%20Query%20-%3E%20Wikidata%0A%20%20%20%20%20%20SERVICE%20%3Chttps%3A%2F%2Fquery.wikidata.org%2Fsparql%3E%20%7B%0A%20%20%20%20%20%20%20%20%20%3FWikidataEntity%20wdt%3AP737%2Fwdt%3AP737%20%3Finfluencedby.%0A%20%20%20%20%20%20%20%20%20%23%20%3Finfluencedby%20widt%3AP734%20%3Fname.%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20OPTIONAL%20%7B%20%20%3Finfluencedby%20wdt%3AP18%20%3Fimage.%7D%0A%20%20%20%20%20%20%7D%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20SERVICE%20wikibase%3Alabel%20%7B%0A%20%20%20%20%20%20%20%20%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22%20.%0A%20%20%20%20%20%20%7D%0A%7D" target="_blank" rel="noopener">Influence networks of authors via ‘federated query’</a></u></li> </ul>
DuckDuckGo: 'Erasure poem' query
<p>A query of "erasure poem" on the search engine DuckDuckGo, on November 18, 2020.</p>
Supreme Military Court in Warsaw 1919-1962 - Query results
<p>Zbiór danych przedstawia kolejne etapy kwerendy archiwalnej i bibliotecznej w ramach programu Miniatura 5 pt. Najwyższy Sąd Wojskowy w Warszawie 1919-1962 Nr. 2021/05/X/HS5/01048 finansowanego przez Narodowe Centrum Nauki.</p>
Evaluation Input Data For The Combined Approach to Query Answering in Horn-ALCHOIQ
<p>This repository contains the evaluation input data for the following publication:</p> <blockquote> <p>David Carral, Irina Dragoste, Markus Krötzsch: <strong>The Combined Approach to Query Answering in Horn-ALCHOIQ.</strong> Proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018).</p> </blockquote> <p>Further details are described therein.</p> <p><strong>Contents</strong><br> The repository contains the following directories:<br> - <strong>input-files</strong>: The input files used in the evaluation, both for our method (using RDFox) and for Konclude reasoner.<br> These are partitions of LUMB, Reactome, Uniprot and UOBM ontologies.<br> - <strong>RDFox_dependency</strong>: The RDFox reasoner used in our prototype implementation</p>
Raptor@GenomeBiology: Query Files
<table> <thead> <tr> <th scope="col">Filename</th> <th scope="col">Compressed size</th> <th scope="col">Uncompressed size</th> </tr> </thead> <tbody> <tr> <td>query_file.1K.fa.zst</td> <td>7.0 MiB</td> <td>28 MiB</td> </tr> <tr> <td>query_file.1K.fastq.zst</td> <td>7.7 MiB</td> <td>52 MiB</td> </tr> <tr> <td>query_file.1M.fa.zst</td> <td>70 MiB</td> <td>278 MiB</td> </tr> <tr> <td>query_file.1M.fastq.zst</td> <td>77 MiB</td> <td>519 MiB</td> </tr> <tr> <td>query_file.5M.fa.zst</td> <td>348 MiB</td> <td>1.4 GiB</td> </tr> <tr> <td>query_file.5M.fastq.zst</td> <td>381 MiB</td> <td>2.6 GiB</td> </tr> <tr> <td>query_file.10M.fa.zst</td> <td>615 MiB</td> <td>2.8 GiB</td> </tr> <tr> <td>query_file.10M.fastq.zst</td> <td>670 MiB</td> <td>5.1 GiB</td> </tr> </tbody> </table> <p> </p> <table> <thead> <tr> <th scope="col">Filename</th> <th scope="col">SHA256 compressed</th> </tr> </thead> <tbody> <tr> <td>query_file.1K.fa.zst</td> <td>087b030d2018d66e0580e76739041b6e5e5bba92836c940425c32a83bebd4079</td> </tr> <tr> <td>query_file.1K.fastq.zst</td> <td>6735a16521aac4aa490b891c1c86d930f028247b0fc79d9ea258edbf74cad251</td> </tr> <tr> <td>query_file.1M.fa.zst</td> <td>6e75c9ae3a773591f397979dfcf9fbd9f1283b37a681055aa6074576783dfd0f</td> </tr> <tr> <td>query_file.1M.fastq.zst</td> <td>558dea66e348eff1adc030f3fc8989af476ef9a92aa587085bd22825a8af576d</td> </tr> <tr> <td>query_file.5M.fa.zst</td> <td>4071b288434169379fb046bc49f7ee9f01a45972e333b7146f51b6e3dc00138c</td> </tr> <tr> <td>query_file.5M.fastq.zst</td> <td>37f8db71ee07833f51031d92c0ac8da1c9b70f39369672e1fe4b503cf8f1279d</td> </tr> <tr> <td>query_file.10M.fa.zst</td> <td>fa22332e5227b2d3cc9c3c6f954269d89726e446a8bde7011be281006e9dd1bb</td> </tr> <tr> <td>query_file.10M.fastq.zst</td> <td>8f4f0238cfaf05f4580ca4bf80c462f03c4870f32f336b94af31904799d33a7d</td> </tr> </tbody> </table> <p> </p> <table> <thead> <tr> <th scope="col">Filename</th> <th scope="col">SHA256 uncompressed</th> </tr> </thead> <tbody> <tr> <td>query_file.1K.fa.zst</td> <td>dfbbb7b4d37ab4fe406ad2a37583de4deabc8ee67f1d62e50fa27124ea821bec</td> </tr> <tr> <td>query_file.1K.fastq.zst</td> <td>f8b0f17f04db748cff73cdbdbb8aef227ba239acd6a5c99faae0e3b74d06cd1e</td> </tr> <tr> <td>query_file.1M.fa.zst</td> <td>845ad455550fa11de737f5f36cd81842a9949dd6e86a1d56987feb448155cb81</td> </tr> <tr> <td>query_file.1M.fastq.zst</td> <td>55553b21eda74c4f5bf9a9960640ec0c80144a9123354b826c186ebd7438f30b</td> </tr> <tr> <td>query_file.5M.fa.zst</td> <td>5e8e4c625f37c2419bf81ca876c94e799efa7c5783240ace15b78c045fcbb9a3</td> </tr> <tr> <td>query_file.5M.fastq.zst</td> <td>65ff2c129cc5209d492e4af84fef3091379dd52ae7bc325a6fa3cd4ca3208606</td> </tr> <tr> <td>query_file.10M.fa.zst</td> <td>2f19cd74c0b85cb2746a9c65ac2930201e3498ba4750e2a4e1e1c376c7e23af9</td> </tr> <tr> <td>query_file.10M.fastq.zst</td> <td>1f4dc264d4069cfbf0a86f5b0acdbcb1b11733e1a050697279729a21b632d071</td> </tr> </tbody> </table> <p> </p>
Evaluation input for The Combined Approach to Query Answering in Horn-ALCHOIQ (Carral, Dragoste, Krötzsch, in proceedings of KR 2018)
<p>This repository contains the input data for the evaluation presented in the following publication:</p> <blockquote> <p>David Carral, Irina Dragoste, Markus Krötzsch: <strong>The Combined Approach to Query Answering in Horn-ALCHOIQ.</strong> Proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018).</p> </blockquote> <p>Together with the materials in https://github.com/knowsys/eval-combined-approach-horn-alchoiq, the input data here provides all the necessary tools and datasets to reproduce the experiments described in this paper.<br> <br> Contents:<br> - <strong>input_files_for_Konclude </strong>- input data for the experiments that use Konclude tool<br> - <strong>input_files_for_RDFox </strong>- input data for the experiments that use our prototype (https://github.com/knowsys/eval-combined-approach-horn-alchoiq/tree/master/combined-approach), which is based on RDFox tool<br> - <strong>RDFox_dependency </strong>- the RDFox reasoner version used in our prototype implementation</p>
Sparql query
<pre>"results": { "bindings": [ { "archprop": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Lantfridus'_tombstone" }, "currentLocation": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Museo_Archeologico_Nazionale_di_Venezia" }, "label": { "type": "literal", "xml:lang": "it", "value": "Lastra sepolcrale di Lanfrido" }, "labelLoc": { "type": "literal", "xml:lang": "it", "value": "Museo Archeologico Nazionale di Venezia" } }, { "archprop": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Castelvint_fort" }, "currentLocation": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Mel" }, "label": { "type": "literal", "xml:lang": "it", "value": "Rocca di Castelvint" }, "labelLoc": { "type": "literal", "xml:lang": "it", "value": "Mel" } }, { "archprop": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Golden_Cross_from_Ceneda" }, "currentLocation": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Kunsthistorisches_Museum_Wien" }, "label": { "type": "literal", "xml:lang": "it", "value": "Crocetta Aurea Cenedese" }, "labelLoc": { "type": "literal", "xml:lang": "it", "value": "Kunsthistorisches Museum Wien" } }, { "archprop": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Casteldardo_fort" }, "currentLocation": { "type": "uri", "value": "http://www.semanticweb.org/utente/ontologies/2023//OntoVE_Archeo#Trichiana" }, "label": { "type": "literal", "xml:lang": "it", "value": "Casteldardo struttura di fortificazione" }, "labelLoc": { "type": "literal", "xml:lang": "it", "value": "Trichiana" } } ] }</pre>
How User Language Affects Conflict Fatality Estimates in ChatGPT, Query script and dataset
<p>*both authors contributed equally</p> <p>Automated query script for automated language bias studies in GPT 3-5</p> <p>Dataset of the paper "How User Language Affects Conflict Fatality Estimates in ChatGPT" preprint available on ArXiv</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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