polyglots/English-NER-70_10_20 · Datasets at Hugging Face

input listlengths 2 305	output listlengths 2 305	instructions stringclasses 1 value
[ "Construction", "of", "RB", "side", "abutment", "&", "Spillway", "construction", "were", "completed", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "(", "a", ")", "Attitude", "Development", "Programs", "Three", "Attitude", "Development", "Programs", "were", "carried", "out", "for", "three", "districts", "in", "order", "to", "create", "public", "service", "employees", "who", "were", "committed", "to", "the",...	[ "O", "O", "O", "B-MISC", "I-MISC", "O", "B-MISC", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "When", "contributing", "money", "to", "beneficiaries", ",", "each", "beneficiary", "is", "paid", "Rs", ".", "1,000", "/", "-", "for", "4", "months", "period", "through", "the", "Divisional", "Secretariat", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "United", "Nations", "Development", "Program", "(", "UNDP", ")", "–", "Strengthening", "Enforcement", "of", "the", "Law", ",", "Access", "to", "Justice", "and", "Social", "Integration", "Project", "This", "Project", "which", "commenced", "its", "activities", "in...	[ "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Two", "days", "viz", ".", ",", "05.08.2015", "and", "06.08.2015", "were", "allocated", "to", "mark", "them", "." ]	[ "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "However", ",", "the", "Government", "was", "able", "to", "limit", "the", "actual", "expenditure", "to", "1370", "billion", ",", "slightly", "lower", "than", "the", "original", "estimated", "1470.8", "billion", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "In", "the", "area", "of", "internal", "capacity", "building", ",", "the", "Institute", "made", "a", "significant", "achievement", "by", "establishing", "a", "RCCB", "testing", "facility", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Mr", ".", "C.", "Pathmanathan", ",", "Professor", "in", "History", ",", "University", "of", "Peradeniya", "and", "Mr.", "Vethachchalam", ",", "Associate", "Professor", "in", "Archaeology", ",", "University", "of", "Tamilnadu", ",", "India", "conducted", "lectur...	[ "O", "O", "B-PER", "I-PER", "O", "B-MISC", "I-MISC", "I-MISC", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "B-PER", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-LOC", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Commercial", "Agreement", "has", "been", "signed", "with", "a", "China", "Company", "for", "implementing", "the", "project", "under", "lump", "sum", "fixed", "price", "for", "US", "$", "690", "million", "in", "November", "2014", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "B-LOC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Ref.", "Balayogi", "Swamy", ",", "president", "of", "Thirumurugan", "Thiruvakku", "Thirupeedam", ",", "Malaysia", "participated", "as", "chief", "guest", "and", "Hon.", "M.K.P.", "Dissanayake", ",", "Secretary", ",", "Ministry", "of", "Buddhasasana", "and", "Cult...	[ "O", "B-PER", "I-PER", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-LOC", "O", "O", "O", "O", "O", "O", "B-PER", "I-PER", "O", "B-MISC", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "O",...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Furthermore", ",", "it", "has", "Writ", "jurisdiction", "rights", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Foreign", "Nature", "of", "Training", "Number", "of", "Officers", "Training", "(", "including", "judges", ")", "Conferences", "Approval", "of", "loan", "Category", "of", "Loan", "Number", "Amount", "(", "Rs", ".", ")" ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "4.1", "In", "terms", "of", "Article", "31", "(", "3", ")", "(", "A", ")", "of", "the", "Constitution", ",", "two", "years", "prior", "to", "the", "end", "of", "his", "term", "of", "office", ",", "His", "Excellency", "the", "President", ",", "Mahinda...	[ "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-PER", ...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "main", "purpose", "of", "the", "Legal", "Aid", "Center", "is", "to", "provide", "the", "necessary", "legal", "assistance", "in", "litigation", "." ]	[ "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "This", "situation", "will", "be", "exacerbated", "by", "the", "impending", "climate", "change", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "3", ".", "Statement", "of", "Compliance", "Accounting", "convention", "of", "the", "National", "Human", "Resources", "Development", "Council", "of", "Sri", "Lanka", "is", "prepared", "in", "accordance", "with", "the", "Sri", "Lanka", "Public", "Sector", "Accoun...	[ "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Project", "Component", "2", ":", "Increase", "climate", "resilience", "of", "Infrastructure", "This", "component", "supports", "to", "implement", "urgent", "climate", "risk", "mitigation", "investments", "identified", "and", "prioritized", "to", ":" ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Activities", "Facilitation", "of", "distribution", "of", "cow", "Units", "of", "measurement", "Number", "Quantity", "Facilitation", "of", "the", "construction", "of", "cattle", "sheds", "Number", "Facilitation", "of", "growing", "of", "CO3", "grass", "Hectares", ...	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "I-LOC", "O", "O", "O", "O", "B-LOC", "I-LOC", "I...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Samanala", "Kanda", "which", "is", "situated", "on", "the", "southern", "part", "is", "2237.3", "m", "in", "height", "." ]	[ "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "2.3.2", "Awareness", "Program", "An", "Awareness", "program", "was", "held", "on", "28th", "September", "2015", "with", "the", "chairmanship", "of", "GA", ",", "Badulla", "." ]	[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-LOC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "At", "district", "level", ",", "certificates", "and", "cash", "awarded", "to", "161", "students", "got", "first", "place", "and", "received", "Rs", ".3000", "per", "each", ",", "144", "students", "got", "second", "place", "and", "received", "Rs", ".", "20...	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "B-MISC", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "B-MISC", "O", "O", "O", ...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Constructions", "of", "field", "canals", "and", "other", "infrastructure", "facilities", "are", "in", "progress", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "There", "are", "37", "Labour", "Tribunals", "functioning", "under", "the", "Secretariat", "of", "the", "Tribunal", "of", "Labour", "." ]	[ "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "amount", "is", "Rs", ".", "14.382", "million", "and", "the", "Government", "of", "Sri", "Lanka", "has", "allocated", "Rs", ".", "235", "million", "for", "the", "incentives", "of", "the", "officers", "of", "the", "institutions", "participating", "in",...	[ "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "5", ".", "Awareness", "and", "Cultural", "Programmes" ]	[ "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "8.2", ".", "In", "terms", "of", "the", "Local", "Authorities", "Elections", "Ordinance", "(", "Chapter", "262", ")", "as", "amended", "by", "the", "Local", "Authorities", "Elections", "(", "Amendment", ")", "Act", "No", ".", "22", "of", "2012", ",", "ev...	[ "B-MISC", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Introduction", "of", "antennas", "All", "necessary", "information", "of", "manufacturing", "500", "MHz", "Corner", "Reflector", "Antenna", "&", "200", "MHz", "Yagi", "Antenna", "Introduction", "and", "design", "of", "Booster", "circuit", "Workshop", "on", "Mobile...	[ "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "B-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "O", "O", ...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Public", "Services", "National", "Security", "and", "Law", "Enforcement", "Human", "Resources", "Infrastructure", "Finance", "Social", "Security", "Environment", "Real", "Economy", "Staff", "Numbers", "of", "Officers", "under", "the", "following", "service", "levels"...	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MI...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Community", "Mediation", ",", "School", "Mediation", ",", "and", "other", "awareness", "programs", "are", "also", "being", "conducted", "by", "Program", "Assistants", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "I", "take", "this", "opportunity", "to", "add", "a", "few", "words", "to", "the", "Performance", "Report", "and", "Annual", "Accounts", "for", "2014", "of", "the", "Department", "of", "Hindu", "Religious", "and", "Cultural", "Affairs", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "10.2.6", ".", "Mr", ".", "Suranga", "Ambagahatenne", ",", "Assistant", "Commissioner", "of", "Elections", "of", "Badulla", "participated", "in", "the", "Capacity", "Building", "Training", "Programme", "held", "in", "India", "from", "17.11.2015", "to", "26.11.2015...	[ "B-MISC", "O", "O", "O", "B-PER", "I-PER", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "B-LOC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-LOC", "O", "B-MISC", "O", "B-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "I", ".", "Number", "of", "times", "conducted", "District", "Secretariat", "-", "Kandy" ]	[ "B-MISC", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Conducting", "a", "Tamil", "medium", "scholarship", "seminar", "program", "in", "the", "Four", "Gravets", "Divisional", "Secretariat", "area", "." ]	[ "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-LOC", "I-LOC", "I-LOC", "I-LOC", "I-LOC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Awards", "Won", "The", "Institute", "has", "won", "the", "World", "Education", "Summit", "Awards", "for", "Best", "Innovation", "in", "Open", "and", "Distance", "Learning", "was", "awarded", "to", "this", "institute", "." ]	[ "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Objectives", "and", "functions", "The", "main", "objective", "of", "the", "Law", "Commission", "is", "to", "promote", "legal", "reform", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Sri", "Lanka", "been", "selected", "by", "the", "United", "Nations", "Economic", "&", "Social", "Commission", "for", "Asia", "and", "the", "Pacific", "(", "UNESCAP", ")", "as", "the", "first", "Pilot", "Country", "for", "implementation", "of", "the", "5", ...	[ "B-LOC", "I-LOC", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC",...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Learning", "while", "earning", "system", "must", "be", "introduced", "to", "reduce", "financial", "problems", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "As", "a", "whole", ",", "an", "agricultural", "economic", "pattern", "can", "be", "seen", "in", "Kandy", "District", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Subsequently", ",", "for", "the", "balance", "remaining", "of", "Rs", ".", "926,000", "/", "-", ",", "the", "cheque", ",", "which", "is", "bearing", "the", "number", "343314", "has", "been", "given", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "6.3.2", ".", "New", "members", "of", "the", "Performance", "Law", "Commission", "have", "been", "appointed", "from", "01.01.2015", "to", "31.12.2015", "." ]	[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "07", ".", "Provincial", "Councils", "Elections", "Act", ",", "No", ".", "2", "of", "1988", "No", "Provincial", "Council", "Election", "was", "held", "in", "the", "year", "2015", "and", "only", "the", "vacancies", "were", "filled", "." ]	[ "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "It", "was", "implemented", "under", "the", "supervision", "of", "the", "Ministry", "of", "Irrigation", "and", "Water", "Resources", "Management", "through", "the", "Department", "of", "Irrigation", ",", "Mahaweli", "Development", "Authority", ",", "Road", "Develo...	[ "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "O", ...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "Institute", "has", "a", "mandate", "to", "provide", ",", "promote", "and", "develop", "among", "persons", "presently", "engaged", "in", "Agriculture", "and", "Agro-Technology", ",", "higher", "education", "in", "the", "discipline", "of", "Agro-Technology",...	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "I-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Accordingly", ",", "approximately", "98", "briefs", "have", "been", "translated", "." ]	[ "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "In", "addition", ",", "06", "meetings", "of", "the", "Board", "of", "Directors", "were", "conducted", "in", "2011", ",", "at", "the", "meetings", ",", "a", "large", "number", "of", "staff", "reports", "are", "examined", "and", "reviewed", "and", "decision...	[ "O", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "Auditorium", "belonging", "to", "the", "District", "Secretariat", ",", "Galle", "and", "located", "at", "the", "Baladaksha", "Road", "had", "been", "destroyed", "by", "the", "tsunami", ",", "which", "occurred", "on", "26.12.2004", ",", "This", "was", ...	[ "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O", "B-LOC", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", ...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "10.2", "Foreign" ]	[ "B-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "This", "Institute", "has", "so", "far", "conducted", "a", "number", "of", "training", "programs", "for", "officers", "and", "employees", "performing", "their", "duties", "in", "the", "field", "of", "justice", "with", "the", "following", "objectives", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Rs", ".", "0.785", "million", "was", "spent", "to", "conduct", "785", "awareness", "programmes", "on", "elder", "protection", "for", "the", "children", "attending", "sunday", "schools", "centring", "157", "Divisional", "Secretariat", "Divisions", "." ]	[ "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "B-ORG", "I-ORG", "I-ORG", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "project", "can", "be", "divided", "into", "four", "parts", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "A", "survey", "on", "school", "dropouts", "We", "know", "that", "students", "leave", "school", "due", "to", "different", "reasons", "." ]	[ "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "3.2.11", ".", "Prior", "to", "the", "commencement", "of", "the", "enumeration", ",", "steps", "were", "taken", "to", "inform", "all", "recognized", "political", "parties", "to", "appoint", "representatives", "on", "their", "behalf", "to", "participate", "in", ...	[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Revenue", "Head", "Revenue", "Accounting", "Officer", "Registrar", "General", "Description", "Registration", "Fee", "Income", "Collected", "in", "2015", "(", "Rs", ".", "Cents", ")", "Forestry", "Conservation", "Private", "Timber", "Transport", "Secretary", "of", ...	[ "B-MISC", "I-MISC", "B-MISC", "I-MISC", "I-MISC", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "B-M...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "(", "b", ")", "Section", "114", "of", "Tax", "Act", "No", "10", "of", "2006", "." ]	[ "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Recommendation", "for", "the", "DSRP", "is", "to", "be", "obtained", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "(", "iii", ")", "Expected", "expenses", "in", "preparing", "the", "estimation", "for", "Elders", "Day", "Celebration", "were", "not", "spent", "and", "it", "has", "been", "instructed", "to", "be", "concerned", "in", "the", "preparation", "of", "estimations", ...	[ "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "4", ".", "Operational", "Reviews", "4.1", "Performance", "The", "performance", "of", "the", "Authority", "as", "against", "the", "targets", "is", "given", "below", "." ]	[ "B-MISC", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "2.3", "Ground", "water", "studies", "at", "Badulla", "Pilot", "Area" ]	[ "B-MISC", "O", "O", "O", "O", "B-LOC", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "participants", "are", "levied", "only", "a", "nominal", "sum", "to", "cover", "the", "core", "expenses", "like", "hall", "charges", "-", "preparation", "of", "literature", "and", "covering", "allowances", "for", "external", "speakers", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "While", "there", "were", "64", "recognized", "political", "parties", "at", "the", "time", "of", "declaring", "the", "Parliamentary", "Election", ",", "only", "35", "political", "parties", "contested", "." ]	[ "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "In", "addition", ",", "the", "National", "Budget", "Department", "was", "responsible", "in", "releasing", "the", "funds", "timely", "for", "the", "projects", "and", "programmes", "approved", "by", "the", "Cabinet", "ensuring", "their", "smooth", "implementation",...	[ "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Therefore", ",", "this", "study", "is", "formulated", "to", "identify", "groundwater", "potential", "areas", "that", "can", "be", "utilized", "for", "small", "scale", "irrigated", "agriculture", ",", "drinking", ",", "and", "industrial", "purposes", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Therefore", ",", "obtaining", "the", "services", "of", "elder", "protection", "voluntary", "workers", "with", "more", "confidence", "has", "become", "possible", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "3.2.9", ".", "Although", "it", "was", "decided", "at", "the", "inception", "to", "complete", "the", "field", "activities", "related", "to", "the", "revision", "which", "commenced", "on", "15th", "May", "2015", ",", "by", "October", "2015", "and", "certify",...	[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", ...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Paying", "consultancy", "allowance", "for", "conducting", "training", "on", "mobility", "and", "orientation" ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Workshops", "conducted", "under", "the", "graduate", "survey", "01", ")", "Date", "23", "/", "10", "/", "2013", "Venue", ":", "Hector", "Kobbekaduwa", "Agrarian", "Research", "and", "Training", "Institute", ".", "Participants", ":", "Graduates", "(", "34", ...	[ "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "Institute", "has", "been", "able", "to", "make", "itself", "a", "self", "sustainable", "unit", "largely", "due", "to", "the", "income", "generated", "through", "the", "sales", "of", "Tissue", "Cultured", "Banana", "Plants", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "10", ".", "Training", "Program", "on", "Office", "Procedures" ]	[ "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "group", "consisted", "of", "about", "20", "personnel", "and", "the", "course", "content", "was", "customized", "to", "their", "requirements", "on", "the", "topic", "of", "both", "theory", "and", "practical", "sessions", "." ]	[ "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "4.8", "Following", "steps", "were", "taken", "to", "ensure", "the", "conduct", "of", "a", "free", "and", "fair", "election", "in", "accordance", "with", "the", "17th", "Amendment", "to", "the", "Constitution", "." ]	[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "After", "implementation", "the", "project", "will", "provide", "annually", "154", "MCM", "water", "for", "industrial", "development", "in", "Greater", "Hambantota", "area", ",", "124", "MCM", "of", "drinking", "water", "for", "25", "Divisional", "Secretariats", ...	[ "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "I-LOC", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "B-LOC", "O", "B-LOC", "O", "O", "B-LOC", "O", "O", "B-MISC"...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "Treasury", "recognized", "an", "aggregate", "sum", "for", "this", "instrument", "during", "the", "budget", "formulation", "process", "considering", "the", "historical", "trends", "in", "public", "expenditure", "and", "budget", "deficits", "and", "other", "...	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "In", "the", "future", "too", ",", "the", "needs", "of", "the", "people", "of", "the", "Galle", "District", "will", "be", "fulfilled", "with", "maximum", "efficiency", "for", "the", "development", "of", "the", "District", "by", "my", "staff", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Having", "studied", "this", "situation", ",", "the", "Board", "of", "Directors", "has", "granted", "approval", "to", "sell", "04", "old", "vehicles", "and", "procure", "4", "new", "vehicles", "on", "lease", "." ]	[ "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "4.1.8", ".", "Payment", "Details", "of", "Line", "Ministries", "and", "Other", "Departments", "In", "addition", "to", "the", "payments", "under", "Expenditure", "Summary", "261", ",", "total", "expenditure", "incurred", "by", "the", "District", "Secretariat", "...	[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O", "B-LOC", "O", "B-MISC", "I-MISC", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O"...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Increased", "diversions", "from", "Polgolla", "diversion", "and", "Bowatenna", "reservoir", "to", "fulfill", "downstream", "requirements", "at", "Minneriya", ",", "Giritale", ",", "Kaudulla", ",", "Kantale", ",", "Huruluwewa", ",", "TissaWewa", ",", "Nachchaduwa", ...	[ "O", "O", "O", "B-MISC", "I-MISC", "O", "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "The", "disabled", "young", "children", "between", "the", "ages", "of", "16", "–", "35", "will", "be", "recruited", "to", "follow", "these", "training", "courses", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Study", "on", "P", "Cygni", "type", "stars", "The", "P", "Cygni", "type", "stars", "have", "expanding", "atmospheres", "and", "the", "studies", "of", "the", "star", "have", "revealed", "a", "unique", "spectral", "feature", "due", "to", "the", "Doppler", "...	[ "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-M...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "At", "present", ",", "first", "batch", "of", "students", "are", "following", "the", "Higher", "Diploma", "in", "Agro-technology", "and", "others", "are", "following", "the", "Diploma", "." ]	[ "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Taking", "steps", "to", "update", "the", "website", "of", "the", "Authority" ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Those", "standards", "require", "that", "we", "plan", "and", "perform", "the", "audit", "to", "obtain", "reasonable", "assurance", "that", "the", "financial", "statements", "are", "free", "from", "material", "misstatements", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "A", "General", "Knowledge", "Competitive", "Examination", "was", "conducted", "on", "28th", "June", "2014", "in", "160", "exam", "centers", "Island", "wide", "for", "the", "students", "of", "Aranery", "School", "and", "around", "69,783", "students", "sat", "f...	[ "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "Arrangements", "have", "been", "made", "not", "to", "do", "such", "shortcomings", "in", "future", "." ]	[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "5.10", "In", "terms", "of", "the", "Elections", "(", "Special", "Provisions", ")", "Act", "No", ".", "14", "of", "2014", "prior", "to", "the", "issue", "of", "a", "ballot", "paper", "at", "the", "polling", "station", ",", "the", "voter", "has", "to", ...	[ "B-MISC", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O",...	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...
[ "1", ".", "CNLA", "-", "Computer", "Networking", "LInux", "Administration", "2012", "October", "13", "-", "2013", "January", "26" ]	[ "B-MISC", "O", "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "B-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC" ]	You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Construction", "of", "RB", "side", "abutment", "&", "Spillway", "construction", "were", "completed", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "(", "a", ")", "Attitude", "Development", "Programs", "Three", "Attitude", "Development", "Programs", "were", "carried", "out", "for", "three", "districts", "in", "order", "to", "create", "public", "service", "employees", "who", "were", "committed", "to", "the",...

[ "O", "O", "O", "B-MISC", "I-MISC", "O", "B-MISC", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "When", "contributing", "money", "to", "beneficiaries", ",", "each", "beneficiary", "is", "paid", "Rs", ".", "1,000", "/", "-", "for", "4", "months", "period", "through", "the", "Divisional", "Secretariat", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "United", "Nations", "Development", "Program", "(", "UNDP", ")", "–", "Strengthening", "Enforcement", "of", "the", "Law", ",", "Access", "to", "Justice", "and", "Social", "Integration", "Project", "This", "Project", "which", "commenced", "its", "activities", "in...

[ "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Two", "days", "viz", ".", ",", "05.08.2015", "and", "06.08.2015", "were", "allocated", "to", "mark", "them", "." ]

[ "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "However", ",", "the", "Government", "was", "able", "to", "limit", "the", "actual", "expenditure", "to", "1370", "billion", ",", "slightly", "lower", "than", "the", "original", "estimated", "1470.8", "billion", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "In", "the", "area", "of", "internal", "capacity", "building", ",", "the", "Institute", "made", "a", "significant", "achievement", "by", "establishing", "a", "RCCB", "testing", "facility", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Mr", ".", "C.", "Pathmanathan", ",", "Professor", "in", "History", ",", "University", "of", "Peradeniya", "and", "Mr.", "Vethachchalam", ",", "Associate", "Professor", "in", "Archaeology", ",", "University", "of", "Tamilnadu", ",", "India", "conducted", "lectur...

[ "O", "O", "B-PER", "I-PER", "O", "B-MISC", "I-MISC", "I-MISC", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "B-PER", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-LOC", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Commercial", "Agreement", "has", "been", "signed", "with", "a", "China", "Company", "for", "implementing", "the", "project", "under", "lump", "sum", "fixed", "price", "for", "US", "$", "690", "million", "in", "November", "2014", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "B-LOC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Ref.", "Balayogi", "Swamy", ",", "president", "of", "Thirumurugan", "Thiruvakku", "Thirupeedam", ",", "Malaysia", "participated", "as", "chief", "guest", "and", "Hon.", "M.K.P.", "Dissanayake", ",", "Secretary", ",", "Ministry", "of", "Buddhasasana", "and", "Cult...

[ "O", "B-PER", "I-PER", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-LOC", "O", "O", "O", "O", "O", "O", "B-PER", "I-PER", "O", "B-MISC", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "O",...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Furthermore", ",", "it", "has", "Writ", "jurisdiction", "rights", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Foreign", "Nature", "of", "Training", "Number", "of", "Officers", "Training", "(", "including", "judges", ")", "Conferences", "Approval", "of", "loan", "Category", "of", "Loan", "Number", "Amount", "(", "Rs", ".", ")" ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "4.1", "In", "terms", "of", "Article", "31", "(", "3", ")", "(", "A", ")", "of", "the", "Constitution", ",", "two", "years", "prior", "to", "the", "end", "of", "his", "term", "of", "office", ",", "His", "Excellency", "the", "President", ",", "Mahinda...

[ "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-PER", ...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "main", "purpose", "of", "the", "Legal", "Aid", "Center", "is", "to", "provide", "the", "necessary", "legal", "assistance", "in", "litigation", "." ]

[ "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "This", "situation", "will", "be", "exacerbated", "by", "the", "impending", "climate", "change", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "3", ".", "Statement", "of", "Compliance", "Accounting", "convention", "of", "the", "National", "Human", "Resources", "Development", "Council", "of", "Sri", "Lanka", "is", "prepared", "in", "accordance", "with", "the", "Sri", "Lanka", "Public", "Sector", "Accoun...

[ "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Project", "Component", "2", ":", "Increase", "climate", "resilience", "of", "Infrastructure", "This", "component", "supports", "to", "implement", "urgent", "climate", "risk", "mitigation", "investments", "identified", "and", "prioritized", "to", ":" ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Activities", "Facilitation", "of", "distribution", "of", "cow", "Units", "of", "measurement", "Number", "Quantity", "Facilitation", "of", "the", "construction", "of", "cattle", "sheds", "Number", "Facilitation", "of", "growing", "of", "CO3", "grass", "Hectares", ...

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "I-LOC", "O", "O", "O", "O", "B-LOC", "I-LOC", "I...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Samanala", "Kanda", "which", "is", "situated", "on", "the", "southern", "part", "is", "2237.3", "m", "in", "height", "." ]

[ "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "2.3.2", "Awareness", "Program", "An", "Awareness", "program", "was", "held", "on", "28th", "September", "2015", "with", "the", "chairmanship", "of", "GA", ",", "Badulla", "." ]

[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-LOC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "At", "district", "level", ",", "certificates", "and", "cash", "awarded", "to", "161", "students", "got", "first", "place", "and", "received", "Rs", ".3000", "per", "each", ",", "144", "students", "got", "second", "place", "and", "received", "Rs", ".", "20...

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "B-MISC", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "B-MISC", "O", "O", "O", ...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Constructions", "of", "field", "canals", "and", "other", "infrastructure", "facilities", "are", "in", "progress", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "There", "are", "37", "Labour", "Tribunals", "functioning", "under", "the", "Secretariat", "of", "the", "Tribunal", "of", "Labour", "." ]

[ "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "amount", "is", "Rs", ".", "14.382", "million", "and", "the", "Government", "of", "Sri", "Lanka", "has", "allocated", "Rs", ".", "235", "million", "for", "the", "incentives", "of", "the", "officers", "of", "the", "institutions", "participating", "in",...

[ "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "5", ".", "Awareness", "and", "Cultural", "Programmes" ]

[ "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "8.2", ".", "In", "terms", "of", "the", "Local", "Authorities", "Elections", "Ordinance", "(", "Chapter", "262", ")", "as", "amended", "by", "the", "Local", "Authorities", "Elections", "(", "Amendment", ")", "Act", "No", ".", "22", "of", "2012", ",", "ev...

[ "B-MISC", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Introduction", "of", "antennas", "All", "necessary", "information", "of", "manufacturing", "500", "MHz", "Corner", "Reflector", "Antenna", "&", "200", "MHz", "Yagi", "Antenna", "Introduction", "and", "design", "of", "Booster", "circuit", "Workshop", "on", "Mobile...

[ "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "B-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "O", "O", ...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Public", "Services", "National", "Security", "and", "Law", "Enforcement", "Human", "Resources", "Infrastructure", "Finance", "Social", "Security", "Environment", "Real", "Economy", "Staff", "Numbers", "of", "Officers", "under", "the", "following", "service", "levels"...

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MI...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Community", "Mediation", ",", "School", "Mediation", ",", "and", "other", "awareness", "programs", "are", "also", "being", "conducted", "by", "Program", "Assistants", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "I", "take", "this", "opportunity", "to", "add", "a", "few", "words", "to", "the", "Performance", "Report", "and", "Annual", "Accounts", "for", "2014", "of", "the", "Department", "of", "Hindu", "Religious", "and", "Cultural", "Affairs", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "10.2.6", ".", "Mr", ".", "Suranga", "Ambagahatenne", ",", "Assistant", "Commissioner", "of", "Elections", "of", "Badulla", "participated", "in", "the", "Capacity", "Building", "Training", "Programme", "held", "in", "India", "from", "17.11.2015", "to", "26.11.2015...

[ "B-MISC", "O", "O", "O", "B-PER", "I-PER", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "B-LOC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-LOC", "O", "B-MISC", "O", "B-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "I", ".", "Number", "of", "times", "conducted", "District", "Secretariat", "-", "Kandy" ]

[ "B-MISC", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Conducting", "a", "Tamil", "medium", "scholarship", "seminar", "program", "in", "the", "Four", "Gravets", "Divisional", "Secretariat", "area", "." ]

[ "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-LOC", "I-LOC", "I-LOC", "I-LOC", "I-LOC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Awards", "Won", "The", "Institute", "has", "won", "the", "World", "Education", "Summit", "Awards", "for", "Best", "Innovation", "in", "Open", "and", "Distance", "Learning", "was", "awarded", "to", "this", "institute", "." ]

[ "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Objectives", "and", "functions", "The", "main", "objective", "of", "the", "Law", "Commission", "is", "to", "promote", "legal", "reform", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Sri", "Lanka", "been", "selected", "by", "the", "United", "Nations", "Economic", "&", "Social", "Commission", "for", "Asia", "and", "the", "Pacific", "(", "UNESCAP", ")", "as", "the", "first", "Pilot", "Country", "for", "implementation", "of", "the", "5", ...

[ "B-LOC", "I-LOC", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC",...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Learning", "while", "earning", "system", "must", "be", "introduced", "to", "reduce", "financial", "problems", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "As", "a", "whole", ",", "an", "agricultural", "economic", "pattern", "can", "be", "seen", "in", "Kandy", "District", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Subsequently", ",", "for", "the", "balance", "remaining", "of", "Rs", ".", "926,000", "/", "-", ",", "the", "cheque", ",", "which", "is", "bearing", "the", "number", "343314", "has", "been", "given", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "6.3.2", ".", "New", "members", "of", "the", "Performance", "Law", "Commission", "have", "been", "appointed", "from", "01.01.2015", "to", "31.12.2015", "." ]

[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "07", ".", "Provincial", "Councils", "Elections", "Act", ",", "No", ".", "2", "of", "1988", "No", "Provincial", "Council", "Election", "was", "held", "in", "the", "year", "2015", "and", "only", "the", "vacancies", "were", "filled", "." ]

[ "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "It", "was", "implemented", "under", "the", "supervision", "of", "the", "Ministry", "of", "Irrigation", "and", "Water", "Resources", "Management", "through", "the", "Department", "of", "Irrigation", ",", "Mahaweli", "Development", "Authority", ",", "Road", "Develo...

[ "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "I-ORG", "I-ORG", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "O", ...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "Institute", "has", "a", "mandate", "to", "provide", ",", "promote", "and", "develop", "among", "persons", "presently", "engaged", "in", "Agriculture", "and", "Agro-Technology", ",", "higher", "education", "in", "the", "discipline", "of", "Agro-Technology",...

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "I-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Accordingly", ",", "approximately", "98", "briefs", "have", "been", "translated", "." ]

[ "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "In", "addition", ",", "06", "meetings", "of", "the", "Board", "of", "Directors", "were", "conducted", "in", "2011", ",", "at", "the", "meetings", ",", "a", "large", "number", "of", "staff", "reports", "are", "examined", "and", "reviewed", "and", "decision...

[ "O", "O", "O", "B-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "Auditorium", "belonging", "to", "the", "District", "Secretariat", ",", "Galle", "and", "located", "at", "the", "Baladaksha", "Road", "had", "been", "destroyed", "by", "the", "tsunami", ",", "which", "occurred", "on", "26.12.2004", ",", "This", "was", ...

[ "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O", "B-LOC", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", ...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "10.2", "Foreign" ]

[ "B-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "This", "Institute", "has", "so", "far", "conducted", "a", "number", "of", "training", "programs", "for", "officers", "and", "employees", "performing", "their", "duties", "in", "the", "field", "of", "justice", "with", "the", "following", "objectives", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Rs", ".", "0.785", "million", "was", "spent", "to", "conduct", "785", "awareness", "programmes", "on", "elder", "protection", "for", "the", "children", "attending", "sunday", "schools", "centring", "157", "Divisional", "Secretariat", "Divisions", "." ]

[ "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "B-ORG", "I-ORG", "I-ORG", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "project", "can", "be", "divided", "into", "four", "parts", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "A", "survey", "on", "school", "dropouts", "We", "know", "that", "students", "leave", "school", "due", "to", "different", "reasons", "." ]

[ "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "3.2.11", ".", "Prior", "to", "the", "commencement", "of", "the", "enumeration", ",", "steps", "were", "taken", "to", "inform", "all", "recognized", "political", "parties", "to", "appoint", "representatives", "on", "their", "behalf", "to", "participate", "in", ...

[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Revenue", "Head", "Revenue", "Accounting", "Officer", "Registrar", "General", "Description", "Registration", "Fee", "Income", "Collected", "in", "2015", "(", "Rs", ".", "Cents", ")", "Forestry", "Conservation", "Private", "Timber", "Transport", "Secretary", "of", ...

[ "B-MISC", "I-MISC", "B-MISC", "I-MISC", "I-MISC", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "B-M...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "(", "b", ")", "Section", "114", "of", "Tax", "Act", "No", "10", "of", "2006", "." ]

[ "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Recommendation", "for", "the", "DSRP", "is", "to", "be", "obtained", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "(", "iii", ")", "Expected", "expenses", "in", "preparing", "the", "estimation", "for", "Elders", "Day", "Celebration", "were", "not", "spent", "and", "it", "has", "been", "instructed", "to", "be", "concerned", "in", "the", "preparation", "of", "estimations", ...

[ "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "4", ".", "Operational", "Reviews", "4.1", "Performance", "The", "performance", "of", "the", "Authority", "as", "against", "the", "targets", "is", "given", "below", "." ]

[ "B-MISC", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "2.3", "Ground", "water", "studies", "at", "Badulla", "Pilot", "Area" ]

[ "B-MISC", "O", "O", "O", "O", "B-LOC", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "participants", "are", "levied", "only", "a", "nominal", "sum", "to", "cover", "the", "core", "expenses", "like", "hall", "charges", "-", "preparation", "of", "literature", "and", "covering", "allowances", "for", "external", "speakers", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "While", "there", "were", "64", "recognized", "political", "parties", "at", "the", "time", "of", "declaring", "the", "Parliamentary", "Election", ",", "only", "35", "political", "parties", "contested", "." ]

[ "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "In", "addition", ",", "the", "National", "Budget", "Department", "was", "responsible", "in", "releasing", "the", "funds", "timely", "for", "the", "projects", "and", "programmes", "approved", "by", "the", "Cabinet", "ensuring", "their", "smooth", "implementation",...

[ "O", "O", "O", "O", "B-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Therefore", ",", "this", "study", "is", "formulated", "to", "identify", "groundwater", "potential", "areas", "that", "can", "be", "utilized", "for", "small", "scale", "irrigated", "agriculture", ",", "drinking", ",", "and", "industrial", "purposes", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Therefore", ",", "obtaining", "the", "services", "of", "elder", "protection", "voluntary", "workers", "with", "more", "confidence", "has", "become", "possible", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "3.2.9", ".", "Although", "it", "was", "decided", "at", "the", "inception", "to", "complete", "the", "field", "activities", "related", "to", "the", "revision", "which", "commenced", "on", "15th", "May", "2015", ",", "by", "October", "2015", "and", "certify",...

[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", ...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Paying", "consultancy", "allowance", "for", "conducting", "training", "on", "mobility", "and", "orientation" ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Workshops", "conducted", "under", "the", "graduate", "survey", "01", ")", "Date", "23", "/", "10", "/", "2013", "Venue", ":", "Hector", "Kobbekaduwa", "Agrarian", "Research", "and", "Training", "Institute", ".", "Participants", ":", "Graduates", "(", "34", ...

[ "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "B-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "I-ORG", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "Institute", "has", "been", "able", "to", "make", "itself", "a", "self", "sustainable", "unit", "largely", "due", "to", "the", "income", "generated", "through", "the", "sales", "of", "Tissue", "Cultured", "Banana", "Plants", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "10", ".", "Training", "Program", "on", "Office", "Procedures" ]

[ "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "group", "consisted", "of", "about", "20", "personnel", "and", "the", "course", "content", "was", "customized", "to", "their", "requirements", "on", "the", "topic", "of", "both", "theory", "and", "practical", "sessions", "." ]

[ "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "4.8", "Following", "steps", "were", "taken", "to", "ensure", "the", "conduct", "of", "a", "free", "and", "fair", "election", "in", "accordance", "with", "the", "17th", "Amendment", "to", "the", "Constitution", "." ]

[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "After", "implementation", "the", "project", "will", "provide", "annually", "154", "MCM", "water", "for", "industrial", "development", "in", "Greater", "Hambantota", "area", ",", "124", "MCM", "of", "drinking", "water", "for", "25", "Divisional", "Secretariats", ...

[ "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "I-LOC", "O", "B-MISC", "I-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "B-LOC", "O", "B-LOC", "O", "O", "B-LOC", "O", "O", "B-MISC"...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "Treasury", "recognized", "an", "aggregate", "sum", "for", "this", "instrument", "during", "the", "budget", "formulation", "process", "considering", "the", "historical", "trends", "in", "public", "expenditure", "and", "budget", "deficits", "and", "other", "...

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "In", "the", "future", "too", ",", "the", "needs", "of", "the", "people", "of", "the", "Galle", "District", "will", "be", "fulfilled", "with", "maximum", "efficiency", "for", "the", "development", "of", "the", "District", "by", "my", "staff", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Having", "studied", "this", "situation", ",", "the", "Board", "of", "Directors", "has", "granted", "approval", "to", "sell", "04", "old", "vehicles", "and", "procure", "4", "new", "vehicles", "on", "lease", "." ]

[ "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "4.1.8", ".", "Payment", "Details", "of", "Line", "Ministries", "and", "Other", "Departments", "In", "addition", "to", "the", "payments", "under", "Expenditure", "Summary", "261", ",", "total", "expenditure", "incurred", "by", "the", "District", "Secretariat", "...

[ "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O", "B-LOC", "O", "B-MISC", "I-MISC", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "O"...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Increased", "diversions", "from", "Polgolla", "diversion", "and", "Bowatenna", "reservoir", "to", "fulfill", "downstream", "requirements", "at", "Minneriya", ",", "Giritale", ",", "Kaudulla", ",", "Kantale", ",", "Huruluwewa", ",", "TissaWewa", ",", "Nachchaduwa", ...

[ "O", "O", "O", "B-MISC", "I-MISC", "O", "B-LOC", "I-LOC", "O", "O", "O", "O", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC", "O", "B-LOC" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "The", "disabled", "young", "children", "between", "the", "ages", "of", "16", "–", "35", "will", "be", "recruited", "to", "follow", "these", "training", "courses", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Study", "on", "P", "Cygni", "type", "stars", "The", "P", "Cygni", "type", "stars", "have", "expanding", "atmospheres", "and", "the", "studies", "of", "the", "star", "have", "revealed", "a", "unique", "spectral", "feature", "due", "to", "the", "Doppler", "...

[ "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "O", "O", "O", "B-MISC", "I-MISC", "I-M...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "At", "present", ",", "first", "batch", "of", "students", "are", "following", "the", "Higher", "Diploma", "in", "Agro-technology", "and", "others", "are", "following", "the", "Diploma", "." ]

[ "O", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Taking", "steps", "to", "update", "the", "website", "of", "the", "Authority" ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Those", "standards", "require", "that", "we", "plan", "and", "perform", "the", "audit", "to", "obtain", "reasonable", "assurance", "that", "the", "financial", "statements", "are", "free", "from", "material", "misstatements", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "A", "General", "Knowledge", "Competitive", "Examination", "was", "conducted", "on", "28th", "June", "2014", "in", "160", "exam", "centers", "Island", "wide", "for", "the", "students", "of", "Aranery", "School", "and", "around", "69,783", "students", "sat", "f...

[ "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "B-ORG", "I-ORG", "O", "O", "B-MISC", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "Arrangements", "have", "been", "made", "not", "to", "do", "such", "shortcomings", "in", "future", "." ]

[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "5.10", "In", "terms", "of", "the", "Elections", "(", "Special", "Provisions", ")", "Act", "No", ".", "14", "of", "2014", "prior", "to", "the", "issue", "of", "a", "ballot", "paper", "at", "the", "polling", "station", ",", "the", "voter", "has", "to", ...

[ "B-MISC", "O", "O", "O", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "I-MISC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O",...

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...

[ "1", ".", "CNLA", "-", "Computer", "Networking", "LInux", "Administration", "2012", "October", "13", "-", "2013", "January", "26" ]

[ "B-MISC", "O", "B-MISC", "O", "B-MISC", "I-MISC", "I-MISC", "I-MISC", "B-MISC", "I-MISC", "I-MISC", "O", "B-MISC", "I-MISC", "I-MISC" ]

You are an NLP assistant whose purpose is to perform Named Entity Recognition (NER). NER involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, miscellaneous entities, and others. You will need to use the tags defined below: O means the w...