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Datasets:
tner
/
ontonotes5

Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K - 100K
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tokens
sequence
tags
sequence
[ "People", "start", "their", "own", "businesses", "for", "many", "reasons", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "But", "a", "chance", "to", "fill", "out", "sales", "-", "tax", "records", "is", "rarely", "one", "of", "them", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ]
[ "Red", "tape", "is", "the", "bugaboo", "of", "small", "business", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "Ironically", ",", "the", "person", "who", "wants", "to", "run", "his", "or", "her", "own", "business", "is", "probably", "the", "active", ",", "results", "-", "oriented", "sort", "most", "likely", "to", "hate", "meeting", "the", "rules", "and", "record", "-", "keeping", "demands", "of", "federal", ",", "state", "and", "local", "regulators", "." ]
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[ "Yet", "every", "business", "owner", "has", "to", "face", "the", "mound", "of", "forms", "and", "regulations", "--", "and", "often", "is", "the", "only", "one", "available", "to", "tackle", "it", "." ]
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[ "There", "is", "hope", "of", "change", "." ]
[ 0, 0, 0, 0, 0, 0 ]
[ "Last", "week", ",", "Sen.", "Malcolm", "Wallop", "-LRB-", "R.", ",", "Wyo", ".", "-RRB-", "held", "hearings", "on", "a", "bill", "to", "strengthen", "an", "existing", "law", "designed", "to", "reduce", "regulatory", "hassles", "for", "small", "businesses", "." ]
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[ "``", "A", "great", "many", "federal", "regulations", "are", "meant", "for", "larger", "entities", "and", "do", "n't", "really", "apply", "to", "small", "businesses", ",", "''", "says", "Marian", "Jacob", ",", "a", "legislative", "aide", "to", "Sen.", "Wallop", "." ]
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[ "Other", "lawmakers", "are", "busy", "trying", "to", "revive", "the", "recently", "lapsed", "Paperwork", "Reduction", "Act", ",", "which", "many", "feel", "benefited", "small", "enterprises", "." ]
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[ "Thus", ",", "optimistic", "entrepreneurs", "await", "a", "promised", "land", "of", "less", "red", "tape", "--", "just", "as", "soon", "as", "Uncle", "Sam", "gets", "around", "to", "arranging", "it", "." ]
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[ "Meanwhile", ",", "they", "tackle", "the", "mounds", "of", "paper", "--", "and", "fantasize", "about", "a", "dream", "world", "where", "bulk", "-", "mail", "postal", "regulations", "and", "government", "inspectors", "are", "banished", "." ]
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[ "To", "find", "out", "what", "red", "tape", "riles", "entrepreneurs", "most", ",", "the", "Journal", "asked", "a", "completely", "unscientific", ",", "random", "sample", "of", "business", "owners", "to", "fantasize", "about", "the", "forms", "and", "regulations", "they", "would", "most", "like", "to", "get", "lost", "in", "the", "mail", "." ]
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[ "Some", "entrepreneurs", "say", "the", "red", "tape", "they", "most", "love", "to", "hate", "is", "red", "tape", "they", "would", "also", "hate", "to", "lose", "." ]
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[ "They", "concede", "that", "much", "of", "the", "government", "meddling", "that", "torments", "them", "is", "essential", "to", "the", "public", "good", ",", "and", "even", "to", "their", "own", "businesses", "." ]
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[ "Rules", "that", "set", "standards", "for", "products", "or", "govern", "business", "behavior", ",", "generally", "the", "best", "regarded", "form", "of", "red", "tape", ",", "``", "create", "a", "level", "playing", "field", "and", "keep", "unscrupulous", "competitors", "away", ",", "''", "says", "Sidney", "West", ",", "president", "of", "TechDesign", "International", "Inc.", ",", "a", "Springfield", ",", "Va.", ",", "business", "that", "designs", "telecommunication", "and", "other", "products", "." ]
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[ "Mr.", "West", "cites", "the", "Federal", "Communications", "Commission", "and", "its", "standards", "for", "telecommunications", "equipment", ":", "``", "They", "monitor", "product", "quality", "and", "prevent", "junk", "from", "flooding", "the", "market", ".", "''" ]
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[ "Some", "gripes", "about", "red", "tape", "are", "predictable", ":", "Architects", "complain", "about", "a", "host", "of", "building", "regulations", ",", "auto", "leasing", "companies", "about", "car", "insurance", "rules", "." ]
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[ "Determining", "when", "handicapped", "access", "is", "required", "can", "be", "a", "nightmare", "for", "architects", ",", "says", "Mark", "Dooling", ",", "president", "of", "Dooling", "&", "Co.", ",", "a", "Newton", ",", "Mass.", ",", "architectural", "firm", "." ]
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[ "There", "is", "such", "a", "maze", "of", "federal", ",", "state", "and", "local", "codes", "that", "``", "building", "inspectors", "are", "backing", "away", "from", "interpreting", "them", ",", "''", "Mr.", "Dooling", "says", "." ]
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[ "Taxi", ",", "leasing", "and", "other", "companies", "that", "maintain", "fleets", "of", "vehicles", "devote", "substantial", "resources", "to", "complying", "with", "state", "insurance", "laws", "and", "a", "host", "of", "agencies", "." ]
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[ "``", "It", "'s", "very", "costly", "and", "time", "-", "consuming", ",", "''", "says", "Phil", "Rosen", ",", "a", "partner", "in", "Fleet", "&", "Leasing", "Management", "Inc.", ",", "a", "Boston", "car", "-", "leasing", "company", "." ]
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[ "One", "senior", "executive", "at", "his", "firm", "spends", "nearly", "20", "%", "of", "his", "time", "on", "insurance", ",", "he", "says", "." ]
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[ "Other", "forms", "of", "red", "tape", "are", "more", "pervasive", "." ]
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[ "The", "most", "onerous", ",", "many", "entrepreneurs", "say", ",", "is", "the", "record", "-", "keeping", "and", "filing", "required", "by", "tax", "authorities", "." ]
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[ "Complying", "with", "environmental", "and", "workplace", "regulations", "runs", "a", "close", "second", "." ]
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[ "But", "gripes", "run", "the", "gamut", "." ]
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[ "Here", "is", "the", "red", "tape", "that", "irks", "surveyed", "business", "owners", "the", "most", ":" ]
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[ "ENVIRONMENTAL", "REGULATIONS", ":" ]
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[ "Next", "to", "medical", "insurance", ",", "``", "costs", "of", "compliance", "''", "are", "the", "fastest", "-", "growing", "expense", "at", "Impco", "Inc.", ",", "a", "Providence", ",", "R.I.", ",", "chemical", "company", "." ]
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[ "Peter", "Gebhard", ",", "the", "company", "'s", "owner", ",", "says", "spending", "on", "regulatory", "paper", "work", "and", "the", "people", "to", "do", "it", "--", "mostly", "to", "comply", "with", "federal", ",", "state", "and", "local", "environmental", "laws", "--", "will", "rise", "almost", "30", "%", "this", "year", "to", "$", "100,000", "." ]
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[ "Mr.", "Gebhard", "adds", "that", "spending", "on", "environmental", "red", "tape", "amounts", "to", "between", "6.5", "%", "and", "7.5", "%", "of", "Impco", "'s", "total", "operating", "expenses", "." ]
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[ "Eastern", "Reproduction", "Corp.", ",", "a", "Waltham", ",", "Mass.", ",", "maker", "of", "thin", "metal", "precision", "parts", ",", "must", "report", "to", "five", "federal", "and", "state", "agencies", "as", "well", "as", "to", "local", "fire", ",", "police", ",", "hospital", "and", "plumbing", "authorities", ",", "says", "Robert", "Maguire", ",", "president", "." ]
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[ "One", "state", "environmental", "regulator", "returned", "a", "report", "because", "``", "it", "was", "n't", "heavy", "enough", ",", "it", "could", "n't", "have", "been", "correct", ",", "''", "Mr.", "Maguire", "says", "." ]
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[ "WITHHOLDING", "RULES", ":" ]
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[ "Employers", "must", "deposit", "withholding", "taxes", "exceeding", "$", "3,000", "within", "three", "days", "after", "payroll", "--", "or", "pay", "stiff", "penalties", "--", "and", "that", "'s", "a", "big", "problem", "for", "small", "businesses", "." ]
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[ "It", "'s", "especially", "nettlesome", "``", "if", "you", "'re", "on", "the", "road", "and", "you", "'re", "the", "one", "responsible", ",", "''", "says", "Eddie", "Brown", ",", "president", "of", "Brown", "Capital", "Management", "Inc.", ",", "a", "Baltimore", "money", "-", "management", "firm", "." ]
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[ "EMPLOYEE", "MANUALS", ":" ]
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[ "Revising", "employee", "manuals", "on", "pensions", ",", "health", "care", "and", "other", "subjects", "costs", "over", "$", "25,000", "a", "year", "for", "Bert", "Giguiere", ",", "president", "of", "Professional", "Agricultural", "Management", "Inc.", ",", "a", "Fresno", ",", "Calif.", ",", "provider", "of", "business", "services", "to", "farmers", "." ]
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[ "An", "employer", "leaves", "itself", "open", "to", "a", "great", "deal", "of", "liability", "if", "its", "employee", "manuals", "do", "n't", "reflect", "the", "most", "recent", "laws", ",", "he", "says", "." ]
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[ "But", "the", "ever", "-", "changing", "laws", "are", "usually", "so", "complicated", "and", "confusing", "that", "``", "you", "need", "professionals", "to", "help", "you", ";", "you", "ca", "n't", "do", "it", "yourself", ",", "''", "he", "adds", "." ]
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[ "PENSION", "AND", "PROFIT", "-", "SHARING", "RULES", ":" ]
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[ "Complying", "with", "these", "is", "enough", "to", "make", "business", "owners", "look", "forward", "to", "their", "own", "pension", "days", "." ]
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[ "Yearly", "changes", "in", "federal", "benefit", "laws", "force", "small", "businesses", "to", "repeatedly", "re-evaluate", "and", "redesign", "existing", "plans", "." ]
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[ "Alice", "Fixx", ",", "who", "runs", "her", "own", "public", "-", "relations", "concern", "in", "New", "York", ",", "says", "she", "has", "had", "to", "overhaul", "her", "pension", "and", "profit", "-", "sharing", "plans", "three", "times", "in", "the", "past", "three", "years", "." ]
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[ "``", "It", "does", "n't", "increase", "benefits", ",", "but", "it", "'s", "costly", "and", "time", "-", "consuming", ",", "''", "Ms.", "Fixx", "says", "." ]
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[ "Compliance", "added", "15", "%", "to", "20", "%", "to", "her", "accounting", "bill", "last", "year", ",", "she", "says", "." ]
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[ "SALES", "TAX", "RECORDS", ":" ]
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[ "Advertising", "agencies", "and", "other", "service", "companies", "are", "exempt", "from", "city", "and", "state", "sales", "tax", "in", "most", "locales", "--", "but", "the", "exemption", "comes", "at", "a", "price", "of", "exhaustive", "records", "and", "rigorous", "reviews", "." ]
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[ "``", "You", "need", "one", "person", "to", "just", "take", "care", "of", "sales", "tax", ",", "''", "says", "Jennie", "Tong", ",", "executive", "vice", "president", "of", "Lee", "Liu", "&", "Tong", "Advertising", "Inc.", ",", "New", "York", "." ]
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[ "How", "would", "this", "bastion", "of", "traditional", "values", "fare", "in", "Ms.", "Bogart", "'s", "iconoclastic", "hands", "?" ]
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[ "She", "held", "her", "fire", "with", "her", "first", "production", "at", "the", "Trinity", "earlier", "this", "season", "." ]
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[ "Hers", "is", "a", "hand", "that", "will", "test", "the", "mettle", "of", "her", "audiences", "." ]
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[ "Along", "the", "way", "there", "also", "are", "lots", "of", "romantic", "dalliances", "." ]
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[ "Wisely", "Ms.", "Bogart", "has", "kept", "Gorky", "'s", "time", "and", "place", "intact", "." ]
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[ "Not", "only", "do", "the", "actors", "stand", "outside", "their", "characters", "and", "make", "it", "clear", "they", "are", "at", "odds", "with", "them", ",", "but", "they", "often", "literally", "stand", "on", "their", "heads", "." ]
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[ "The", "danger", "that", "Ms.", "Bogart", "seems", "to", "be", "courting", "here", "is", "one", "of", "obfuscation", "rather", "than", "rejuvenation", ",", "a", "vision", "so", "at", "odds", "with", "the", "playwright", "'s", "that", "the", "two", "points", "of", "view", "nullify", ",", "rather", "than", "illuminate", ",", "each", "other", "." ]
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[ "Ms.", "Bogart", "'s", "cast", "is", "part", "and", "parcel", "of", "the", "problem", "." ]
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[ "Ed", "Shea", "and", "Barbara", "Orson", "never", "find", "a", "real", "reason", "for", "their", "love", "affair", "as", "the", "foolish", ",", "idealistic", "young", "Vass", "and", "the", "tirelessly", "humanitarian", "doctor", "Maria", "Lvovna", "." ]
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[ "Cynthia", "Strickland", "as", "the", "long", "-", "suffering", "Varvara", "is", "a", "tiresome", "whiner", ",", "not", "the", "inspirational", "counterrevolutionary", "Gorky", "intended", "." ]
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[ "Better", "to", "look", "in", "the", "corners", "for", "performances", "that", "inspire", "or", "amuse", "." ]
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[ "Janice", "Duclos", ",", "in", "addition", "to", "possessing", "one", "of", "the", "evening", "'s", "more", "impressive", "vocal", "instruments", ",", "brings", "an", "unsuspected", "comedic", "touch", "to", "her", "role", "of", "Olga", ",", "everybody", "'s", "favorite", "mom", "." ]
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[ "Marni", "Rice", "plays", "the", "maid", "with", "so", "much", "edge", "as", "to", "steal", "her", "two", "scenes", "." ]
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[ "But", "it", "is", "the", "Trinity", "Rep", "newcomer", ",", "Jonathan", "Fried", "-LRB-", "Zamislov", ",", "the", "paralegal", "-RRB-", "who", "is", "the", "actor", "to", "watch", ",", "whether", "he", "is", "hamming", "it", "up", "while", "conducting", "the", "chamber", "musicians", "or", "seducing", "his", "neighbor", "'s", "wife", "-LRB-", "Becca", "Lish", "-RRB-", "by", "licking", "her", "bosom", "." ]
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[ "Ms.", "de", "Vries", "writes", "frequently", "about", "theater", "." ]
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[ "Yields", "on", "certificates", "of", "deposit", "at", "major", "banks", "were", "little", "changed", "in", "the", "latest", "week", "." ]
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[ "Both", "issues", "are", "among", "the", "most", "popular", "with", "individual", "investors", "." ]
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[ "``", "Because", "of", "shrinkage", "in", "the", "economy", ",", "rates", "can", "be", "expected", "to", "decline", "over", "a", "one", "-", "year", "horizon", ",", "''", "said", "Norberto", "Mehl", ",", "chairman", "of", "Banxquote", "." ]
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[ "Interest", "rates", "generally", "began", "declining", "last", "spring", "after", "moving", "steadily", "upward", "for", "more", "than", "a", "year", "." ]
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[ "The", "average", "yield", "on", "small", "-", "denomination", "three", "-", "month", "CDs", "moved", "up", "two", "-", "hundredths", "of", "a", "percentage", "point", "in", "the", "latest", "week", "to", "7.85", "%", "." ]
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[ "Long", "-", "term", "CDs", "declined", "just", "a", "fraction", "." ]
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[ "The", "average", "yield", "on", "both", "two", "-", "year", "CDs", "and", "five", "-", "year", "CDs", "was", "7.98", "%", "." ]
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Dataset Card for "tner/ontonotes5"

Dataset Summary

Ontonotes5 NER dataset formatted in a part of TNER project.

  • Entity Types: CARDINAL, DATE, PERSON, NORP, GPE, LAW, PERCENT, ORDINAL, MONEY, WORK_OF_ART, FAC, TIME, QUANTITY, PRODUCT, LANGUAGE, ORG, LOC, EVENT

Dataset Structure

Data Instances

An example of train looks as follows.

{
    'tags': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 5, 0, 0, 0, 0, 11, 12, 12, 12, 12, 0, 0, 7, 0, 0, 0, 0, 0],
    'tokens': ['``', 'It', "'s", 'very', 'costly', 'and', 'time', '-', 'consuming', ',', "''", 'says', 'Phil', 'Rosen', ',', 'a', 'partner', 'in', 'Fleet', '&', 'Leasing', 'Management', 'Inc.', ',', 'a', 'Boston', 'car', '-', 'leasing', 'company', '.']
}

Label ID

The label2id dictionary can be found at here.

{
    "O": 0,
    "B-CARDINAL": 1,
    "B-DATE": 2,
    "I-DATE": 3,
    "B-PERSON": 4,
    "I-PERSON": 5,
    "B-NORP": 6,
    "B-GPE": 7,
    "I-GPE": 8,
    "B-LAW": 9,
    "I-LAW": 10,
    "B-ORG": 11,
    "I-ORG": 12, 
    "B-PERCENT": 13,
    "I-PERCENT": 14, 
    "B-ORDINAL": 15, 
    "B-MONEY": 16, 
    "I-MONEY": 17, 
    "B-WORK_OF_ART": 18, 
    "I-WORK_OF_ART": 19, 
    "B-FAC": 20, 
    "B-TIME": 21, 
    "I-CARDINAL": 22, 
    "B-LOC": 23, 
    "B-QUANTITY": 24, 
    "I-QUANTITY": 25, 
    "I-NORP": 26, 
    "I-LOC": 27, 
    "B-PRODUCT": 28, 
    "I-TIME": 29, 
    "B-EVENT": 30,
    "I-EVENT": 31,
    "I-FAC": 32,
    "B-LANGUAGE": 33,
    "I-PRODUCT": 34,
    "I-ORDINAL": 35,
    "I-LANGUAGE": 36
}

Data Splits

name train validation test
ontonotes5 59924 8528 8262

Citation Information 

@inproceedings{hovy-etal-2006-ontonotes,
    title = "{O}nto{N}otes: The 90{\%} Solution",
    author = "Hovy, Eduard  and
      Marcus, Mitchell  and
      Palmer, Martha  and
      Ramshaw, Lance  and
      Weischedel, Ralph",
    booktitle = "Proceedings of the Human Language Technology Conference of the {NAACL}, Companion Volume: Short Papers",
    month = jun,
    year = "2006",
    address = "New York City, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N06-2015",
    pages = "57--60",
}
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Edit dataset card
Repository:
T-NER
Paper:
aclanthology.org
Dataset:
Ontonotes5
Domain:
News
Number of Entity:
8
Size of downloaded dataset files:
17.5 MB
Size of the auto-converted Parquet files:
4.71 MB
Number of rows:
76,714

Models trained or fine-tuned on tner/ontonotes5

Browse 10 models trained on this dataset