YurtsAI/named_entity_recognition

该数据集主要用于命名实体识别（NER）任务，包含两个主要特征：tokens和ner_tags。tokens是文本中的单词序列，而ner_tags是对应的命名实体标签序列。标签涵盖了多个类别，如艺术、建筑、事件、地点、组织、人物、产品、日期时间等。数据集分为训练集、测试集和评估集，分别包含4308、538和538个示例。

This dataset is primarily used for Named Entity Recognition (NER) tasks and contains two main features: tokens and ner_tags. tokens is a sequence of words in the text, while ner_tags is the corresponding sequence of named entity tags. The tags cover a wide range of categories such as art, building, event, location, organization, person, product, datetime, etc. The dataset is divided into training, test, and evaluation sets, containing 4308, 538, and 538 examples respectively.

原始信息汇总

数据集概述

特征

• tokens: 字符串序列
• ner_tags: 命名实体识别标签序列
  • 标签名称:
    • 0: O
    • 1: B-art-broadcastprogram
    • 2: I-art-broadcastprogram
    • 3: B-art-film
    • 4: I-art-film
    • 5: B-art-music
    • 6: I-art-music
    • 7: B-art-other
    • 8: I-art-other
    • 9: B-art-painting
    • 10: I-art-painting
    • 11: B-art-writtenart
    • 12: I-art-writtenart
    • 13: B-building-airport
    • 14: I-building-airport
    • 15: B-building-hospital
    • 16: I-building-hospital
    • 17: B-building-hotel
    • 18: I-building-hotel
    • 19: B-building-library
    • 20: I-building-library
    • 21: B-building-other
    • 22: I-building-other
    • 23: B-building-restaurant
    • 24: I-building-restaurant
    • 25: B-building-sportsfacility
    • 26: I-building-sportsfacility
    • 27: B-building-theater
    • 28: I-building-theater
    • 29: B-event-attack/battle/war/militaryconflict
    • 30: I-event-attack/battle/war/militaryconflict
    • 31: B-event-disaster
    • 32: I-event-disaster
    • 33: B-event-election
    • 34: I-event-election
    • 35: B-event-other
    • 36: I-event-other
    • 37: B-event-protest
    • 38: I-event-protest
    • 39: B-event-sportsevent
    • 40: I-event-sportsevent
    • 41: B-location-gpe
    • 42: I-location-gpe
    • 43: B-location-bodiesofwater
    • 44: I-location-bodiesofwater
    • 45: B-location-island
    • 46: I-location-island
    • 47: B-location-mountain
    • 48: I-location-mountain
    • 49: B-location-other
    • 50: I-location-other
    • 51: B-location-park
    • 52: I-location-park
    • 53: B-location-road/railway/highway/transit
    • 54: I-location-road/railway/highway/transit
    • 55: B-organization-company
    • 56: I-organization-company
    • 57: B-organization-education
    • 58: I-organization-education
    • 59: B-organization-government/governmentagency
    • 60: I-organization-government/governmentagency
    • 61: B-organization-media/newspaper
    • 62: I-organization-media/newspaper
    • 63: B-organization-other
    • 64: I-organization-other
    • 65: B-organization-politicalparty
    • 66: I-organization-politicalparty
    • 67: B-organization-religion
    • 68: I-organization-religion
    • 69: B-organization-showorganization
    • 70: I-organization-showorganization
    • 71: B-organization-sportsleague
    • 72: I-organization-sportsleague
    • 73: B-organization-sportsteam
    • 74: I-organization-sportsteam
    • 75: B-other-astronomything
    • 76: I-other-astronomything
    • 77: B-other-award
    • 78: I-other-award
    • 79: B-other-biologything
    • 80: I-other-biologything
    • 81: B-other-chemicalthing
    • 82: I-other-chemicalthing
    • 83: B-other-currency
    • 84: I-other-currency
    • 85: B-other-disease
    • 86: I-other-disease
    • 87: B-other-educationaldegree
    • 88: I-other-educationaldegree
    • 89: B-other-god
    • 90: I-other-god
    • 91: B-other-language
    • 92: I-other-language
    • 93: B-other-law
    • 94: I-other-law
    • 95: B-other-livingthing
    • 96: I-other-livingthing
    • 97: B-other-medical
    • 98: I-other-medical
    • 99: B-person-actor
    • 100: I-person-actor
    • 101: B-person-artist/author
    • 102: I-person-artist/author
    • 103: B-person-athlete
    • 104: I-person-athlete
    • 105: B-person-director
    • 106: I-person-director
    • 107: B-person-other
    • 108: I-person-other
    • 109: B-person-politician
    • 110: I-person-politician
    • 111: B-person-scholar
    • 112: I-person-scholar
    • 113: B-person-soldier
    • 114: I-person-soldier
    • 115: B-product-airplane
    • 116: I-product-airplane
    • 117: B-product-car
    • 118: I-product-car
    • 119: B-product-food
    • 120: I-product-food
    • 121: B-product-game
    • 122: I-product-game
    • 123: B-product-other
    • 124: I-product-other
    • 125: B-product-ship
    • 126: I-product-ship
    • 127: B-product-software
    • 128: I-product-software
    • 129: B-product-train
    • 130: I-product-train
    • 131: B-product-weapon
    • 132: I-product-weapon
    • 133: B-datetime-absolute
    • 134: I-datetime-absolute
    • 135: B-datetime-relative
    • 136: I-datetime-relative
    • 137: B-datetime-range
    • 138: I-datetime-range
    • 139: B-datetime-authored
    • 140: I-datetime-authored

数据集划分

• train:
  • 字节数: 5197058
  • 样本数: 4308
• test:
  • 字节数: 652224
  • 样本数: 538
• eval:
  • 字节数: 662721
  • 样本数: 538

数据集大小

• 下载大小: 1124450 字节
• 数据集总大小: 6512003 字节

配置

• config_name: default
  • 数据文件:
    • train: data/train-*
    • test: data/test-*
    • eval: data/eval-*