Datasets:

DFKI-SLT
/

mobie

id stringlengths 21 219	tokens sequence	ner_tags sequence
755276242237218816::0	[ "Werde", "meine", "#Verspätungen", "als", "#Statistik", "mal", "veröffentlichen", "." ]	[ 0, 0, 0, 0, 0, 0, 0, 0 ]
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1108129826844672001::0	[ "#S4", "#RegioNDS", "#Teilausfall", "#Mellendorf", "(", "23.03", ")", ">", "#Bennemühlen", "(", "23.07", ")", "." ]	[ 15, 27, 39, 17, 0, 1, 0, 0, 13, 0, 1, 0, 0 ]
1108129826844672001::1	[ "Grund", ":", "technische", "Störung", "an", "der", "Strecke", "." ]	[ 0, 0, 9, 10, 0, 0, 0, 0 ]
1108129826844672001::2	[ "Bitte", "nutzen", "Sie", "#RB38", "nach", "Soltau", "über", "Bennemühlen", "Abfahrt", ":", "23:08", "Uhr", "vom", "Gleis", "2" ]	[ 0, 0, 0, 15, 0, 13, 0, 17, 0, 0, 37, 38, 0, 0, 23 ]
https://www.presseportal.de/blaulicht/pm/62288/4117034#9@2018-11-15T22:07:09.000+01:00::0	[ "POL", "-", "WI", ":", "Falscher", "Polizeibeamter", "auf", "A66", "festgenommen", "." ]	[ 25, 26, 26, 0, 0, 0, 0, 19, 0, 0 ]
https://www.presseportal.de/blaulicht/pm/62288/4117034#9@2018-11-15T22:07:09.000+01:00::1	[ "PASt", "(", "KvD", ")", "-", "Polizeipräsidium", "Westhessen", "[", "Newsroom", "]", "Wiesbaden", "(", "ots", ")", "-", "15.11.2018", ",", "17:50", "Uhr", ",", "TuR", "Weilbach", ",", "in", "Richtung", "Frankfurt", "am", "Main", "Einer", "Zivilstreife", "der", "Wiesbadener", "Polizei", "fiel", "auf", "dem", "Gelände", "der", "Tank", "-", "und", "Rastanlage", "Weilbach", "ein", "dunkler", "5er", "BMW", ",", "mit", "Frankfurter", "Ortskennung", ",", "auf", "." ]	[ 25, 26, 26, 26, 26, 26, 26, 0, 0, 0, 13, 0, 0, 0, 0, 1, 0, 39, 40, 0, 11, 12, 0, 0, 0, 13, 14, 14, 0, 0, 0, 25, 26, 0, 0, 0, 0, 0, 11, 12, 12, 12, 12, 0, 0, 0, 27, 0, 0, 13, 0, 0, 0, 0 ]
https://www.presseportal.de/blaulicht/pm/62288/4117034#9@2018-11-15T22:07:09.000+01:00::2	[ "Im", "Zuge", "der", "...", "Lesen", "Sie", "hier", "weiter", "...", "Original", "-", "Content", "von", ":", "PASt", "(", "KvD", ")", "-", "Polizeipräsidium", "Westhessen", ",", "übermittelt", "durch", "news", "aktuell" ]	[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 25, 26, 26, 26, 26, 26, 26, 0, 0, 0, 27, 28 ]
http://www.ndr.de/nachrichten/verkehr/index.html#2@2016-05-04T21:02:14.000+02:00::0	[ "Vorsicht", "bitte", "auf", "der", "A28", "Leer", "Richtung", "Oldenburg", "zwischen", "Zwischenahner", "Meer", "und", "Neuenkruge", "liegen", "Gegenstände", "!" ]	[ 0, 0, 0, 0, 19, 13, 0, 13, 0, 11, 12, 0, 11, 0, 0, 0 ]
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1111089830971215872::1	[ "#S7", "fährt", "zwischen", "#Wannsee", "und", "#Potsdam_Hbf", "." ]	[ 15, 0, 0, 17, 0, 17, 0 ]
1111089830971215872::2	[ "nur", "im", "20", "-", "Min", "-", "Takt.", ",", "Züge", "nach", "#Potsdam_Hbf", "." ]	[ 0, 0, 7, 8, 8, 8, 8, 0, 0, 0, 13, 0 ]
1111089830971215872::3	[ "fahren", "ab", "#Wannsee", "zu", "den", "Minuten", "12", ",", "32", ",", "52", "." ]	[ 0, 0, 17, 0, 0, 0, 37, 0, 37, 0, 37, 0 ]
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1110205733730217985::1	[ "Eine", "Tür", "ist", "sichtbar", "als", "defekt", "gekennze", "…" ]	[ 0, 0, 0, 0, 0, 0, 0, 0 ]
1111185208647274501::0	[ "RT", "@SBahn_Stuttgart", ":", "🚨S", "törung🚨", " D", "rzeit s", "eht e", "ne #", "2 R", "chtung F", "lderstadt m", "t e", "ner T", "rstörung i", " S", "g-R", "o", "hr. ", "E" ]	[ 0, 27, 0, 0, 9, 0, 0, 0, 0, 15, 0, 13, 0, 0, 9, 0, 17, 18, 18, 0 ]
1111185208647274501::1	[ " k", "mmt a", "f d", "n L", "nien #", "1, ", "#", "", "" ]	[ 0, 0, 0, 0, 0, 15, 0, 0, 0 ]
1107999871552942083::0	[ "#RE7", "#RegioSH", "#RE", "21070", "#Hamburg", "Hbf", "(", "14:43", ")", "-", "#Flensburg", "(", "16:42", ")", "." ]	[ 15, 27, 15, 16, 17, 18, 0, 37, 0, 0, 17, 0, 37, 0, 0 ]
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1107999871552942083::3	[ "Bitte", "nutzen", "Sie", "ab", "Hamburg", "Hbf", "die", "S3", "bzw", "." ]	[ 0, 0, 0, 0, 17, 18, 0, 15, 0, 0 ]
1107999871552942083::4	[ "S31", "bis", "Hamburg", "-", "Altona", "." ]	[ 15, 0, 17, 18, 18, 0 ]
http://www.ndr.de/nachrichten/verkehr/index.html#8@2016-03-17T01:12:00.000+01:00::0	[ "A20", "Lübeck", "Richtung", "Rostock", "zwischen", "Raststätte", "Fuchsberg", "Süd", "und", "Kreuz", "Rostock", "fährt", "ein", "Schwertransport", ",", "der", "nicht", "überholt", "werden", "kann", "." ]	[ 19, 13, 0, 13, 0, 11, 12, 12, 0, 11, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
671260432699629568::0	[ "RT", "@muellerjuerg", ":", "Bahn", "frei", "für", "die", "Zukunft", ":", "https://t.co/zJv4IA5wKv", "An", "der", "Weltfunkkonferenz", "in", "Genf", "wurden", "verschiedene", "Frequenzen", "neu", "zu", "…" ]	[ 0, 33, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13, 0, 0, 0, 0, 0, 0 ]
http://verkehrsmeldungen.polizei-bw.de//TICRss.ashx?region=BW&id=e380f236-ac5b-441c-aa27-01bed7b113de@2016-03-17T21:40:00.000+01:00::0	[ "Friedrichshafen", "Richtung", "Stockach", "zwischen", "Überlingen", "-", "Aufkirch", "und", "Überlingen", "-", "Goldbach", "Gefahr", "durch", "ein", "totes", "Tier", "auf", "der", "Fahrbahn" ]	[ 13, 0, 13, 0, 11, 12, 12, 0, 11, 12, 12, 0, 0, 0, 0, 0, 0, 0, 0 ]
1109145372537077760::0	[ "#Zuffenhausen", "Heute", "Nachmittag", "ist", "auf", "der", "B27", "auf", "Höhe", "der", "Ausfahrt", "Zuffenhausen", "ein", "Smart", "in", "Brand", "geraten", "." ]	[ 11, 1, 37, 0, 0, 0, 19, 0, 0, 0, 0, 11, 0, 0, 39, 40, 40, 0 ]
1109145372537077760::1	[ "Die", "Bundesstraße", "war", "wegen", "den", "Bergungsarbeiten", "kurzzeitig", "gesperrt", "." ]	[ 0, 19, 0, 0, 0, 9, 0, 39, 0 ]
1109145372537077760::2	[ "Zur", "Pressemeldung", "▶", "https://t.co/D0qQtXXcJF", "Eure", "#Polizei", "#Stuttgart", "https://t.co/J0IAXq7us2" ]	[ 0, 0, 0, 0, 0, 25, 13, 0 ]
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1110876915777368064::2	[ "@SBahnBerlin", "#verkehr", "#potsdam", "https://t.co/OibwP9eb64" ]	[ 27, 0, 13, 0 ]
1112040034172092418::0	[ "Wo", "geht", "es", "den", "heute", "mal", "hin", "?" ]	[ 0, 0, 0, 0, 1, 0, 0, 0 ]
1112040034172092418::1	[ "(", "@", "S", "5", "-", ">", "Frankfurt", "(", "Main", ")", "Hbf", "(", "Tief", ")", ")", "#NowTräwelling", "https://t.co/1qGxRpSf98" ]	[ 0, 0, 15, 16, 0, 0, 13, 14, 14, 14, 14, 14, 14, 14, 0, 0, 0 ]
1108353210773921793::0	[ "@RMVdialog", "@Willy10200", "@NadUndDieNatur", "D.h.", "Entfall", "der", "RB75", "auch", "zwischen", "Bischofsheim", "und", "Wiesbaden", "-", "oder", "?" ]	[ 0, 0, 0, 0, 39, 0, 15, 0, 0, 17, 0, 17, 0, 0, 0 ]
1108353210773921793::1	[ "Ist", "bei", "der", "HLB", "etwas", "uneindeutig", "ausgedrückt", "..." ]	[ 0, 0, 0, 27, 0, 0, 0, 0 ]
631449197435322369::0	[ "RT", "@faznet", ":", "Der", "ägyptische", "Ableger", "des", "Islamischen", "Staats", "hat", "nach", "eigenen", "Angaben", "eine", "kroatische", "Geisel", "ermordet", "http://t.co/C6bQbEAbOh" ]	[ 0, 27, 0, 0, 11, 0, 0, 25, 26, 0, 0, 0, 0, 0, 11, 0, 0, 0 ]
744552884163969025::0	[ "@zeitonline", "wir", "lassen", "unsere", "Gesellschaft", "nicht", "von", "solchen", "Menschen", "verderben", "." ]	[ 27, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
744552884163969025::1	[ "." ]	[ 0 ]
744552884163969025::2	[ "Traditionell", "Orientiert", "!!!" ]	[ 0, 0, 0 ]
1109198606198804480::0	[ "Die", "A57", "bei", "Köln", "ist", "wieder", "frei", ",", "der", "Stau", "hat", "sich", "auch", "schon", "aufgelöst", "." ]	[ 0, 19, 0, 11, 0, 0, 0, 0, 0, 39, 0, 0, 0, 0, 39, 0 ]
1109198606198804480::1	[ "Ihr", "steht", "jetzt", "noch", "auf", "der", "A4", "zwischen", "#Kerpen", "und", "Köln", "sowie", "an", "den", "Nachtbaustellen", "auf", "der", "A4", "zwischen", "#Lind", "und", "Wahn", "und", "der", "A45", "zwischen", "#Freudenberg", "und", "Olpe", "." ]	[ 0, 0, 0, 0, 0, 0, 19, 0, 11, 0, 11, 0, 0, 0, 0, 0, 0, 19, 0, 11, 0, 11, 0, 0, 19, 0, 11, 0, 11, 0 ]
1109198606198804480::2	[ "https://t.co/ZCIdP2XUVx" ]	[ 0 ]
1106541567421136897::0	[ "@SBahnBerlin", "@IGEB_Berlin", "Umfangreiche", "Aus", "-", "und", "Erneuerungsarbeiten", "entlang", "der", "Strecke", "Berlin", "-", "Gesundbrunnen", "–", "Berlin", "-", "Karow", "–", "Bernau", "Entlang", "der", "„", "Stettiner", "Bahn", "“", "stehen", "in", "den", "nächsten", "Jahren", "verschiedene", "Bauvorhaben", "auf", "dem", "Plan", ",", "." ]	[ 27, 25, 0, 9, 0, 0, 9, 0, 0, 0, 17, 18, 18, 0, 17, 18, 18, 0, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 0, 0, 0, 0, 0 ]
1106541567421136897::1	[ "." ]	[ 0 ]
1106541567421136897::2	[ "Ok", ",", "mit", "der", "S2", "wird", "das", "nichts", "mehr", ",", "der", "Nordosten", "für", "Jahre", "gekappt" ]	[ 0, 0, 0, 0, 15, 0, 0, 0, 0, 0, 0, 11, 0, 7, 0 ]
http://www.br-online.de/aktuell/verkehr/verkehr-verkehrsmeldungen-staumeldungen-ID119730167093.xml#17@2019-03-30T20:04:48.757+01:00::0	[ "Service", "S", "-", "Bahn", "München", ":", "." ]	[ 0, 27, 28, 28, 28, 0, 0 ]

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Dataset Card for "MobIE"

Dataset Summary

This script is for loading the MobIE dataset from https://github.com/dfki-nlp/mobie.

MobIE is a German-language dataset which is human-annotated with 20 coarse- and fine-grained entity types and entity linking information for geographically linkable entities. The dataset consists of 3,232 social media texts and traffic reports with 91K tokens, and contains 20.5K annotated entities, 13.1K of which are linked to a knowledge base. A subset of the dataset is human-annotated with seven mobility-related, n-ary relation types, while the remaining documents are annotated using a weakly-supervised labeling approach implemented with the Snorkel framework. The dataset combines annotations for NER, EL and RE, and thus can be used for joint and multi-task learning of these fundamental information extraction tasks.

This version of the dataset loader provides NER tags only. NER tags use the BIO tagging scheme.

For more details see https://github.com/dfki-nlp/mobie and https://aclanthology.org/2021.konvens-1.22/.

Supported Tasks and Leaderboards

Tasks: Named Entity Recognition
Leaderboards:

Languages

German

Dataset Structure

Data Instances

Size of downloaded dataset files: 7.8 MB
Size of the generated dataset: 1.9 MB
Total amount of disk used: 9.7 MB

An example of 'train' looks as follows.

{ 
  'id': 'http://www.ndr.de/nachrichten/verkehr/index.html#2@2016-05-04T21:02:14.000+02:00',
  'tokens': ['Vorsicht', 'bitte', 'auf', 'der', 'A28', 'Leer', 'Richtung', 'Oldenburg', 'zwischen', 'Zwischenahner', 'Meer', 'und', 'Neuenkruge', 'liegen', 'Gegenstände', '!'], 
  'ner_tags': [0, 0, 0, 0, 19, 13, 0, 13, 0, 11, 12, 0, 11, 0, 0, 0]
}

Data Fields

The data fields are the same among all splits.

id: a string feature.
tokens: a list of string features.
ner_tags: a list of classification labels, with possible values including O (0), B-date (1), I-date (2), B-disaster-type (3), I-disaster-type (4), ...

Data Splits

	Train	Dev	Test
MobIE	4785	1082	1210

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

CC BY-SA 4.0 license

Citation Information

@inproceedings{hennig-etal-2021-mobie,
    title = "{M}ob{IE}: A {G}erman Dataset for Named Entity Recognition, Entity Linking and Relation Extraction in the Mobility Domain",
    author = "Hennig, Leonhard  and
      Truong, Phuc Tran  and
      Gabryszak, Aleksandra",
    booktitle = "Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021)",
    month = "6--9 " # sep,
    year = "2021",
    address = {D{\"u}sseldorf, Germany},
    publisher = "KONVENS 2021 Organizers",
    url = "https://aclanthology.org/2021.konvens-1.22",
    pages = "223--227",
}