Datasets:

DFKI-SLT
/

cross_re

doc_key stringlengths 10 12	sentence sequence	ner list	relations list
ai-train-1	[ "Popular", "approaches", "of", "opinion-based", "recommender", "system", "utilize", "various", "techniques", "including", "text", "mining", ",", "information", "retrieval", ",", "sentiment", "analysis", "(", "see", "also", "Multimodal", "sentiment", "analysis", ")", ...	[ { "id-start": 3, "id-end": 5, "entity-type": "product" }, { "id-start": 10, "id-end": 11, "entity-type": "field" }, { "id-start": 13, "id-end": 14, "entity-type": "task" }, { "id-start": 16, "id-end": 17, "entity-type": "task" }, { "id-start": 21, ...	[ { "id_1-start": 3, "id_1-end": 5, "id_2-start": 10, "id_2-end": 11, "relation-type": "part-of", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 3, "id_1-end": 5, "id_2-start": 10, "id_2-end": 11, "relation-type": "usage", "Exp": "", "Un": false,...
ai-train-2	[ "Advocates", "of", "procedural", "representations", "were", "mainly", "centered", "at", "MIT", ",", "under", "the", "leadership", "of", "Marvin", "Minsky", "and", "Seymour", "Papert", "." ]	[ { "id-start": 8, "id-end": 8, "entity-type": "university" }, { "id-start": 14, "id-end": 15, "entity-type": "researcher" }, { "id-start": 17, "id-end": 18, "entity-type": "researcher" } ]	[ { "id_1-start": 14, "id_1-end": 15, "id_2-start": 8, "id_2-end": 8, "relation-type": "physical", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 14, "id_1-end": 15, "id_2-start": 8, "id_2-end": 8, "relation-type": "role", "Exp": "", "Un": false,...
ai-train-3	[ "The", "standard", "interface", "and", "calculator", "interface", "are", "written", "in", "Java", "." ]	[ { "id-start": 9, "id-end": 9, "entity-type": "programlang" } ]	[]
ai-train-4	[ "Octave", "helps", "in", "solving", "linear", "and", "nonlinear", "problems", "numerically", ",", "and", "for", "performing", "other", "numerical", "experiments", "using", "a", "that", "is", "mostly", "compatible", "with", "MATLAB", "." ]	[ { "id-start": 0, "id-end": 0, "entity-type": "product" }, { "id-start": 23, "id-end": 23, "entity-type": "product" } ]	[ { "id_1-start": 0, "id_1-end": 0, "id_2-start": 23, "id_2-end": 23, "relation-type": "related-to", "Exp": "compatible_with", "Un": false, "SA": false } ]
ai-train-5	[ "Variants", "of", "the", "back-propagation", "algorithm", "as", "well", "as", "unsupervised", "methods", "by", "Geoff", "Hinton", "and", "colleagues", "at", "the", "University", "of", "Toronto", "can", "be", "used", "to", "train", "deep", ",", "highly", "nonli...	[ { "id-start": 3, "id-end": 4, "entity-type": "algorithm" }, { "id-start": 8, "id-end": 9, "entity-type": "misc" }, { "id-start": 11, "id-end": 12, "entity-type": "researcher" }, { "id-start": 17, "id-end": 19, "entity-type": "university" } ]	[ { "id_1-start": 3, "id_1-end": 4, "id_2-start": 11, "id_2-end": 12, "relation-type": "origin", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 8, "id_1-end": 9, "id_2-start": 11, "id_2-end": 12, "relation-type": "origin", "Exp": "", "Un": false,...
ai-train-6	[ "or", "equivalently", "using", "DCG", "notation", ":" ]	[ { "id-start": 3, "id-end": 3, "entity-type": "metrics" } ]	[]
ai-train-7	[ "Self-organizing", "maps", "differ", "from", "other", "artificial", "neural", "networks", "as", "they", "apply", "competitive", "learning", "as", "opposed", "to", "error-correction", "learning", "such", "as", "backpropagation", "with", "gradient", "descent", ")", ",...	[ { "id-start": 0, "id-end": 1, "entity-type": "algorithm" }, { "id-start": 5, "id-end": 7, "entity-type": "algorithm" }, { "id-start": 11, "id-end": 12, "entity-type": "algorithm" }, { "id-start": 16, "id-end": 17, "entity-type": "algorithm" }, { "i...	[ { "id_1-start": 0, "id_1-end": 1, "id_2-start": 5, "id_2-end": 7, "relation-type": "type-of", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 0, "id_1-end": 1, "id_2-start": 11, "id_2-end": 12, "relation-type": "usage", "Exp": "part-of?", "Un": ...
ai-train-8	[ "Since", "the", "early", "1990s", ",", "it", "has", "been", "recommended", "by", "several", "authorities", ",", "including", "the", "Audio", "Engineering", "Society", "that", "measurements", "of", "dynamic", "range", "be", "made", "with", "an", "audio", "signa...	[ { "id-start": 15, "id-end": 17, "entity-type": "organisation" }, { "id-start": 27, "id-end": 28, "entity-type": "misc" }, { "id-start": 38, "id-end": 40, "entity-type": "metrics" } ]	[]
ai-train-9	[ "The", "technique", "used", "in", "creating", "eigenfaces", "and", "using", "them", "for", "recognition", "is", "also", "used", "outside", "of", "face", "recognition", ":", "handwriting", "recognition", ",", "lip", "reading", ",", "voice", "recognition", ",", ...	[ { "id-start": 5, "id-end": 5, "entity-type": "misc" }, { "id-start": 16, "id-end": 17, "entity-type": "task" }, { "id-start": 19, "id-end": 20, "entity-type": "task" }, { "id-start": 22, "id-end": 23, "entity-type": "task" }, { "id-start": 25, ...	[ { "id_1-start": 5, "id_1-end": 5, "id_2-start": 16, "id_2-end": 17, "relation-type": "part-of", "Exp": "concept_used_in", "Un": true, "SA": false }, { "id_1-start": 5, "id_1-end": 5, "id_2-start": 19, "id_2-end": 20, "relation-type": "part-of", "Exp": "con...
ai-train-10	[ "The", "National", "Science", "Foundation", "was", "an", "umbrella", "for", "the", "National", "Aeronautics", "and", "Space", "Administration", "(", "NASA", ")", ",", "the", "US", "Department", "of", "Energy", ",", "the", "US", "Department", "of", "Commerce", ...	[ { "id-start": 1, "id-end": 3, "entity-type": "organisation" }, { "id-start": 9, "id-end": 13, "entity-type": "organisation" }, { "id-start": 15, "id-end": 15, "entity-type": "organisation" }, { "id-start": 19, "id-end": 22, "entity-type": "organisation" ...	[ { "id_1-start": 9, "id_1-end": 13, "id_2-start": 1, "id_2-end": 3, "relation-type": "part-of", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 15, "id_1-end": 15, "id_2-start": 9, "id_2-end": 13, "relation-type": "named", "Exp": "", "Un": false,...
ai-train-11	[ "A", "fast", "method", "for", "computing", "maximum", "likelihood", "estimates", "for", "the", "probit", "model", "was", "proposed", "by", "Ronald", "Fisher", "as", "an", "appendix", "to", "Bliss", "'", "work", "in", "1935", "." ]	[ { "id-start": 5, "id-end": 6, "entity-type": "metrics" }, { "id-start": 10, "id-end": 11, "entity-type": "algorithm" }, { "id-start": 15, "id-end": 16, "entity-type": "researcher" }, { "id-start": 21, "id-end": 21, "entity-type": "researcher" } ]	[ { "id_1-start": 5, "id_1-end": 6, "id_2-start": 10, "id_2-end": 11, "relation-type": "part-of", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 15, "id_1-end": 16, "id_2-start": 21, "id_2-end": 21, "relation-type": "related-to", "Exp": "added_append...
ai-train-12	[ "Several", "of", "these", "programs", "are", "available", "online", ",", "such", "as", "Google", "Translate", "and", "the", "SYSTRAN", "system", "that", "powers", "AltaVista", "'s", "BabelFish", "(", "now", "Yahoo", "'s", "Babelfish", "as", "of", "9", "May",...	[ { "id-start": 10, "id-end": 11, "entity-type": "product" }, { "id-start": 14, "id-end": 15, "entity-type": "product" }, { "id-start": 18, "id-end": 18, "entity-type": "organisation" }, { "id-start": 20, "id-end": 20, "entity-type": "product" }, { "...	[ { "id_1-start": 20, "id_1-end": 20, "id_2-start": 14, "id_2-end": 15, "relation-type": "usage", "Exp": "uses_software", "Un": false, "SA": false }, { "id_1-start": 20, "id_1-end": 20, "id_2-start": 18, "id_2-end": 18, "relation-type": "artifact", "Exp": ""...
ai-train-13	[ "In", "2002", "Hutter", ",", "with", "Jürgen", "Schmidhuber", "and", "Shane", "Legg", ",", "developed", "and", "published", "a", "mathematical", "theory", "of", "artificial", "general", "intelligence", "based", "on", "idealised", "intelligent", "agents", "and", ...	[ { "id-start": 2, "id-end": 2, "entity-type": "researcher" }, { "id-start": 5, "id-end": 6, "entity-type": "researcher" }, { "id-start": 8, "id-end": 9, "entity-type": "researcher" }, { "id-start": 18, "id-end": 20, "entity-type": "field" }, { "id-s...	[ { "id_1-start": 2, "id_1-end": 2, "id_2-start": 18, "id_2-end": 20, "relation-type": "related-to", "Exp": "", "Un": true, "SA": false }, { "id_1-start": 2, "id_1-end": 2, "id_2-start": 24, "id_2-end": 25, "relation-type": "related-to", "Exp": "", "Un":...
ai-train-14	[ "The", "most", "common", "way", "is", "using", "the", "so-called", "ROUGE", "(", "Recall-Oriented", "Understudy", "for", "Gisting", "Evaluation", ")", "measure", "." ]	[ { "id-start": 8, "id-end": 8, "entity-type": "metrics" }, { "id-start": 10, "id-end": 14, "entity-type": "metrics" } ]	[ { "id_1-start": 8, "id_1-end": 8, "id_2-start": 10, "id_2-end": 14, "relation-type": "named", "Exp": "", "Un": false, "SA": false } ]
ai-train-15	[ "RapidMiner", "provides", "learning", "schemes", ",", "models", "and", "algorithms", "and", "can", "be", "extended", "using", "R", "and", "Python", "scripts", ".", "David", "Norris", ",", "Bloor", "Research", ",", "November", "13", ",", "2013", "." ]	[ { "id-start": 0, "id-end": 0, "entity-type": "product" }, { "id-start": 13, "id-end": 13, "entity-type": "programlang" }, { "id-start": 15, "id-end": 15, "entity-type": "programlang" }, { "id-start": 18, "id-end": 19, "entity-type": "researcher" }, { ...	[ { "id_1-start": 0, "id_1-end": 0, "id_2-start": 13, "id_2-end": 13, "relation-type": "related-to", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 0, "id_1-end": 0, "id_2-start": 15, "id_2-end": 15, "relation-type": "related-to", "Exp": "", "Un"...
ai-train-16	[ "tity", "contains", "a", "collection", "of", "visualization", "tools", "and", "algorithms", "for", "data", "analysis", "and", "predictive", "modeling", ",", "together", "with", "graphical", "user", "interfaces", "for", "easy", "access", "to", "these", "functions."...	[ { "id-start": 0, "id-end": 0, "entity-type": "product" }, { "id-start": 10, "id-end": 11, "entity-type": "field" }, { "id-start": 13, "id-end": 14, "entity-type": "task" }, { "id-start": 18, "id-end": 20, "entity-type": "misc" }, { "id-start": 32, ...	[ { "id_1-start": 0, "id_1-end": 0, "id_2-start": 10, "id_2-end": 11, "relation-type": "related-to", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 0, "id_1-end": 0, "id_2-start": 13, "id_2-end": 14, "relation-type": "related-to", "Exp": "", "Un"...
ai-train-17	[ "Eurisko", "made", "many", "interesting", "discoveries", "and", "enjoyed", "significant", "acclaim", ",", "with", "his", "paper", "Heuretics", ":", "Theoretical", "and", "Study", "of", "Heuristic", "Rules", "winning", "the", "Best", "Paper", "award", "at", "the"...	[ { "id-start": 0, "id-end": 0, "entity-type": "product" }, { "id-start": 13, "id-end": 20, "entity-type": "misc" }, { "id-start": 23, "id-end": 25, "entity-type": "misc" }, { "id-start": 28, "id-end": 35, "entity-type": "conference" } ]	[ { "id_1-start": 13, "id_1-end": 20, "id_2-start": 0, "id_2-end": 0, "relation-type": "topic", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 13, "id_1-end": 20, "id_2-start": 23, "id_2-end": 25, "relation-type": "win-defeat", "Exp": "", "Un": f...
ai-train-18	[ "To", "allow", "for", "multiple", "entities", ",", "a", "separate", "Hinge", "loss", "is", "computed", "for", "each", "capsule", "." ]	[ { "id-start": 8, "id-end": 9, "entity-type": "metrics" } ]	[]
ai-train-19	[ "With", "the", "emergence", "of", "conversational", "assistants", "such", "as", "Apple", "'s", "Siri", ",", "Amazon", "Alexa", ",", "Google", "Assistant", ",", "Microsoft", "Cortana", ",", "and", "Samsung", "'s", "Bixby", ",", "Voice", "Portals", "can", "now...	[ { "id-start": 8, "id-end": 10, "entity-type": "product" }, { "id-start": 12, "id-end": 13, "entity-type": "product" }, { "id-start": 15, "id-end": 16, "entity-type": "product" }, { "id-start": 18, "id-end": 19, "entity-type": "product" }, { "id-sta...	[ { "id_1-start": 8, "id_1-end": 10, "id_2-start": 26, "id_2-end": 27, "relation-type": "type-of", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 12, "id_1-end": 13, "id_2-start": 26, "id_2-end": 27, "relation-type": "type-of", "Exp": "", "Un": f...
ai-train-20	[ "Examples", "of", "supervised", "learning", "are", "Naive", "Bayes", "classifier", ",", "Support", "vector", "machine", ",", "mixtures", "of", "Gaussians", ",", "and", "network", "." ]	[ { "id-start": 2, "id-end": 3, "entity-type": "field" }, { "id-start": 5, "id-end": 7, "entity-type": "algorithm" }, { "id-start": 9, "id-end": 11, "entity-type": "algorithm" }, { "id-start": 13, "id-end": 15, "entity-type": "algorithm" }, { "id-sta...	[ { "id_1-start": 5, "id_1-end": 7, "id_2-start": 2, "id_2-end": 3, "relation-type": "type-of", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 9, "id_1-end": 11, "id_2-start": 2, "id_2-end": 3, "relation-type": "type-of", "Exp": "", "Un": false, ...
ai-train-21	[ "One", "can", "use", "the", "OSD", "algorithm", "to", "derive", "math", "O", "(", "\\", "sqrt", "{", "T", "}", ")", "/", "math", "regret", "bounds", "for", "the", "online", "version", "of", "Support", "vector", "machine", "for", "classification", ",", ...	[ { "id-start": 4, "id-end": 5, "entity-type": "algorithm" }, { "id-start": 26, "id-end": 28, "entity-type": "algorithm" }, { "id-start": 30, "id-end": 30, "entity-type": "task" }, { "id-start": 35, "id-end": 36, "entity-type": "metrics" } ]	[ { "id_1-start": 4, "id_1-end": 5, "id_2-start": 26, "id_2-end": 28, "relation-type": "part-of", "Exp": "", "Un": true, "SA": false }, { "id_1-start": 35, "id_1-end": 36, "id_2-start": 30, "id_2-end": 30, "relation-type": "usage", "Exp": "", "Un": true,...
ai-train-22	[ "Applications", "include", "object", "recognition", ",", "robotic", "mapping", "and", "navigation", ",", "image", "stitching", ",", "3D", "modeling", ",", "gesture", "recognition", ",", "video", "tracking", ",", "individual", "identification", "of", "wildlife", "a...	[ { "id-start": 2, "id-end": 3, "entity-type": "task" }, { "id-start": 5, "id-end": 6, "entity-type": "task" }, { "id-start": 8, "id-end": 8, "entity-type": "task" }, { "id-start": 10, "id-end": 11, "entity-type": "task" }, { "id-start": 13, "id-...	[]
ai-train-23	[ "A", "number", "of", "groups", "and", "companies", "are", "researching", "pose", "estimation", ",", "including", "groups", "at", "Brown", "University", ",", "Carnegie", "Mellon", "University", ",", "MPI", "Saarbruecken", ",", "Stanford", "University", ",", "the"...	[ { "id-start": 8, "id-end": 9, "entity-type": "task" }, { "id-start": 14, "id-end": 15, "entity-type": "university" }, { "id-start": 17, "id-end": 19, "entity-type": "university" }, { "id-start": 21, "id-end": 22, "entity-type": "university" }, { "i...	[ { "id_1-start": 8, "id_1-end": 9, "id_2-start": 14, "id_2-end": 15, "relation-type": "related-to", "Exp": "", "Un": true, "SA": false }, { "id_1-start": 8, "id_1-end": 9, "id_2-start": 17, "id_2-end": 19, "relation-type": "related-to", "Exp": "", "Un":...
ai-train-24	[ "Sigmoid", "function", "Cross", "entropy", "loss", "is", "used", "for", "predicting", "K", "independent", "probability", "values", "in", "math", "0,1", "/", "math", "." ]	[ { "id-start": 0, "id-end": 4, "entity-type": "metrics" } ]	[]
ai-train-25	[ "He", "held", "the", "Johann", "Bernoulli", "Chair", "of", "Mathematics", "and", "Informatics", "at", "the", "University", "of", "Groningen", "in", "the", "Netherlands", ",", "and", "the", "Toshiba", "Endowed", "Chair", "at", "the", "Tokyo", "Institute", "of",...	[ { "id-start": 3, "id-end": 5, "entity-type": "misc" }, { "id-start": 7, "id-end": 7, "entity-type": "field" }, { "id-start": 9, "id-end": 9, "entity-type": "field" }, { "id-start": 12, "id-end": 14, "entity-type": "university" }, { "id-start": 17, ...	[ { "id_1-start": 3, "id_1-end": 5, "id_2-start": 7, "id_2-end": 7, "relation-type": "topic", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 3, "id_1-end": 5, "id_2-start": 9, "id_2-end": 9, "relation-type": "topic", "Exp": "", "Un": false, "...
ai-train-26	[ "Another", "technique", "particularly", "used", "for", "recurrent", "neural", "network", "s", "is", "the", "long", "short-term", "memory", "(", "LSTM", ")", "network", "of", "1997", "by", "Sepp", "Hochreiter", "&", "Jürgen", "Schmidhuber", "." ]	[ { "id-start": 5, "id-end": 7, "entity-type": "algorithm" }, { "id-start": 11, "id-end": 13, "entity-type": "algorithm" }, { "id-start": 15, "id-end": 15, "entity-type": "algorithm" }, { "id-start": 21, "id-end": 22, "entity-type": "researcher" }, { ...	[ { "id_1-start": 5, "id_1-end": 7, "id_2-start": 11, "id_2-end": 13, "relation-type": "usage", "Exp": "", "Un": true, "SA": false }, { "id_1-start": 11, "id_1-end": 13, "id_2-start": 21, "id_2-end": 22, "relation-type": "origin", "Exp": "", "Un": false,...
ai-train-27	[ "The", "inclusion", "of", "a", "C", "+", "+", "interpreter", "(", "CINT", "until", "version", "5.34", ",", "Cling", "from", "version", "6", ")", "makes", "this", "package", "very", "versatile", "as", "it", "can", "be", "used", "in", "interactive", ",", ...	[ { "id-start": 4, "id-end": 6, "entity-type": "programlang" }, { "id-start": 9, "id-end": 9, "entity-type": "product" }, { "id-start": 14, "id-end": 14, "entity-type": "product" }, { "id-start": 44, "id-end": 44, "entity-type": "product" } ]	[ { "id_1-start": 9, "id_1-end": 9, "id_2-start": 4, "id_2-end": 6, "relation-type": "general-affiliation", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 9, "id_1-end": 9, "id_2-start": 14, "id_2-end": 14, "relation-type": "named", "Exp": "", "U...
ai-train-28	[ "Voice", "user", "interfaces", "that", "interpret", "and", "manage", "conversational", "state", "are", "challenging", "to", "design", "due", "to", "the", "inherent", "difficulty", "of", "integrating", "complex", "natural", "language", "processing", "tasks", "like", ...	[ { "id-start": 0, "id-end": 2, "entity-type": "product" }, { "id-start": 21, "id-end": 23, "entity-type": "field" }, { "id-start": 26, "id-end": 27, "entity-type": "task" }, { "id-start": 29, "id-end": 30, "entity-type": "task" }, { "id-start": 32, ...	[ { "id_1-start": 0, "id_1-end": 2, "id_2-start": 21, "id_2-end": 23, "relation-type": "related-to", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 26, "id_1-end": 27, "id_2-start": 21, "id_2-end": 23, "relation-type": "part-of", "Exp": "", "Un":...
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ai-train-30	[ "Modern", "Windows", "desktop", "systems", "can", "use", "SAPI", "4", "and", "SAPI", "5", "components", "to", "support", "speech", "synthesis", "and", "speech", "." ]	[ { "id-start": 1, "id-end": 3, "entity-type": "product" }, { "id-start": 6, "id-end": 7, "entity-type": "product" }, { "id-start": 9, "id-end": 10, "entity-type": "product" }, { "id-start": 14, "id-end": 15, "entity-type": "task" }, { "id-start": 17...	[ { "id_1-start": 1, "id_1-end": 3, "id_2-start": 6, "id_2-end": 7, "relation-type": "usage", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 1, "id_1-end": 3, "id_2-start": 9, "id_2-end": 10, "relation-type": "usage", "Exp": "", "Un": false, ...
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ai-train-90	[ "Unimation", "purchased", "Victor", "Scheinman", "'", "s", "Vicarm", "Inc.", "in", "1977", ",", "and", "with", "Scheinman", "'s", "help", ",", "the", "company", "created", "and", "began", "producing", "the", "Programmable", "Universal", "Machine", "for", "Asse...	[ { "id-start": 0, "id-end": 0, "entity-type": "organisation" }, { "id-start": 2, "id-end": 3, "entity-type": "researcher" }, { "id-start": 6, "id-end": 7, "entity-type": "organisation" }, { "id-start": 13, "id-end": 13, "entity-type": "researcher" }, { ...	[ { "id_1-start": 0, "id_1-end": 0, "id_2-start": 6, "id_2-end": 7, "relation-type": "related-to", "Exp": "purchases", "Un": false, "SA": false }, { "id_1-start": 2, "id_1-end": 3, "id_2-start": 13, "id_2-end": 13, "relation-type": "named", "Exp": "same", ...
ai-train-91	[ "J48", "is", "an", "open", "source", "Java", "implementation", "of", "the", "C4.5", "algorithm", "in", "the", "Weka", "data", "mining", "tool", "." ]	[ { "id-start": 0, "id-end": 0, "entity-type": "product" }, { "id-start": 5, "id-end": 5, "entity-type": "programlang" }, { "id-start": 9, "id-end": 10, "entity-type": "algorithm" }, { "id-start": 13, "id-end": 16, "entity-type": "product" } ]	[ { "id_1-start": 0, "id_1-end": 0, "id_2-start": 5, "id_2-end": 5, "relation-type": "general-affiliation", "Exp": "", "Un": false, "SA": false }, { "id_1-start": 0, "id_1-end": 0, "id_2-start": 9, "id_2-end": 10, "relation-type": "origin", "Exp": "implement...
ai-train-92	[ "The", "2004", "SSIM", "paper", "has", "been", "cited", "over", "20,000", "times", "according", "to", "Google", "Scholar", ",", "It", "also", "received", "the", "IEEE", "Signal", "Processing", "Society", "Sustained", "Impact", "Award", "for", "2016", ",", "i...	[ { "id-start": 2, "id-end": 2, "entity-type": "metrics" }, { "id-start": 12, "id-end": 13, "entity-type": "product" }, { "id-start": 19, "id-end": 25, "entity-type": "misc" } ]	[ { "id_1-start": 2, "id_1-end": 2, "id_2-start": 12, "id_2-end": 13, "relation-type": "win-defeat", "Exp": "", "Un": false, "SA": false } ]
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Dataset Card for CrossRE

Dataset Summary

CrossRE is a new, freely-available crossdomain benchmark for RE, which comprises six distinct text domains and includes multilabel annotations. It includes the following domains: news, politics, natural science, music, literature and artificial intelligence. The semantic relations are annotated on top of CrossNER (Liu et al., 2021), a cross-domain dataset for NER which contains domain-specific entity types. The dataset contains 17 relation labels for the six domains: PART-OF, PHYSICAL, USAGE, ROLE, SOCIAL, GENERAL-AFFILIATION, COMPARE, TEMPORAL, ARTIFACT, ORIGIN, TOPIC, OPPOSITE, CAUSE-EFFECT, WIN-DEFEAT, TYPEOF, NAMED, and RELATED-TO.

For details, see the paper: https://arxiv.org/abs/2210.09345

Supported Tasks and Leaderboards

More Information Needed

Languages

The language data in CrossRE is in English (BCP-47 en)